[FreeCourseSite.com] Udemy - Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4

磁力链接/BT种子名称

[FreeCourseSite.com] Udemy - Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4

磁力链接/BT种子简介

种子哈希：908167937e50d0b36f50e084ad0a1dda4712e8f2
文件大小： 12.75G
已经下载：8447次
下载速度：极快
收录时间：2024-01-02
最近下载：2025-09-28

移花宫入口

移花宫.com邀月.com怜星.com花无缺.comyhgbt.icuyhgbt.top

磁力链接下载

magnet:?xt=urn:btih:908167937E50D0B36F50E084AD0A1DDA4712E8F2
推荐使用PIKPAK网盘下载资源，10TB超大空间，不限制资源，无限次数离线下载，视频在线观看

下载BT种子文件

磁力链接 迅雷下载 PIKPAK在线播放 世界之窗 91视频 含羞草 欲漫涩 逼哩逼哩 成人快手 51品茶 抖阴破解版 极乐禁地 91短视频 抖音Max TikTok成人版 PornHub 听泉鉴鲍 少女日记 草榴社区 哆哔涩漫 呦乐园 萝莉岛 悠悠禁区 悠悠禁区 拔萝卜 疯马秀

最近搜索

文件列表

  • 16. Visualizing What CNN's Learn/6. Filter and Class Maximization.mp4 163.6 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/2. Loading Pre-trained Networks in PyTorch (ResNets, DenseNets, MobileNET, VGG19).mp4 161.2 MB
  • 2. Download Code and Setup Colab/1.1 Code - Modern Computer Vision_05_06_2022.zip 158.3 MB
  • 9. OpenCV Projects/6. Neural Style Transfer with OpenCV.mp4 150.0 MB
  • 22. Google DeepStream and Neural Style Transfer/5. Neural Style Transfer in Keras.mp4 147.9 MB
  • 4. OpenCV - Image Segmentation/2. Moments, Sorting, Approximating and Matching Contours.mp4 146.6 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/1. Implementing LeNet and AlexNet in Keras.mp4 146.1 MB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/5. DeepFace - Age, Gender, Emotion, Ethnicity and Face Recognition.mp4 138.8 MB
  • 21. Transfer Learning and Fine Tuning/4. Keras Feature Extraction.mp4 138.2 MB
  • 29. Gun Detector - Scaled-YoloV4/1. Gun Detector - Scaled-YoloV4.mp4 134.7 MB
  • 21. Transfer Learning and Fine Tuning/5. PyTorch Fine Tuning.mp4 127.5 MB
  • 2. Download Code and Setup Colab/1.2 ebook slides - Modern Computer Vision.pdf 127.5 MB
  • 9. OpenCV Projects/3. OCR with PyTesseract and EasyOCR (Text Detection).mp4 125.3 MB
  • 3. OpenCV - Image Operations/9. Thresholding, Binarization & Adaptive Thresholding.mp4 122.9 MB
  • 4. OpenCV - Image Segmentation/1. Contours - Drawing, Hierarchy and Modes.mp4 122.8 MB
  • 19. Using Callbacks in Keras and PyTorch/2. Cats vs Dogs Classifier using Callbacks in PyTorch.mp4 120.6 MB
  • 3. OpenCV - Image Operations/6. Scaling, Re-sizing, Interpolations and Cropping.mp4 120.5 MB
  • 19. Using Callbacks in Keras and PyTorch/3. Cats vs Dogs Classifier using Callbacks in Keras.mp4 120.3 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/3. Loading Pre-trained Networks in Keras (ResNets, DenseNets, MobileNET, VGG19).mp4 116.8 MB
  • 5. OpenCV - Haar Cascade Classifiers/1. Face and Eye Detection with Haar Cascade Classifiers.mp4 115.6 MB
  • 24. Generative Adversarial Networks (GANs)/4. Use Cases for GANs.mp4 113.4 MB
  • 15. Improving Models and Advanced CNN Design/12. Training a Fashion Classifider (FNIST) with Regularization using PyTorch.mp4 113.3 MB
  • 16. Visualizing What CNN's Learn/3. Keras Filter Visualization and Activations.mp4 112.4 MB
  • 20. PyTorch Lightning/3. Auto Batch and Learning Rate Selection plus Tensorboards.mp4 111.7 MB
  • 21. Transfer Learning and Fine Tuning/7. PyTorch Feature Extraction.mp4 108.4 MB
  • 12. Building CNNs in PyTorch/5. Building our Model.mp4 107.3 MB
  • 24. Generative Adversarial Networks (GANs)/7. Super Resolution GAN.mp4 107.2 MB
  • 24. Generative Adversarial Networks (GANs)/5. Keras DCGAN with MNIST.mp4 105.8 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/5. Getting the Rank-N Accuracy in PyTorch.mp4 102.7 MB
  • 48. Image Captioning with Keras/1. Image Captioning with Keras.mp4 100.8 MB
  • 12. Building CNNs in PyTorch/7. Training Your Model.mp4 100.7 MB
  • 15. Improving Models and Advanced CNN Design/10. Training a Fashion Classifider (FNIST) with Regularization using Keras.mp4 100.7 MB
  • 21. Transfer Learning and Fine Tuning/3. Transfer Learning and Fine Tuning with Keras.mp4 100.7 MB
  • 7. OpenCV - Motion and Object Tracking/2. Object Tracking with Optical Flow.mp4 99.8 MB
  • 3. OpenCV - Image Operations/1. Getting Started with OpenCV4.mp4 99.3 MB
  • 52. Point Cloud Segmentation Using PointNet/1. Point Cloud Segmentation Using PointNet.mp4 96.5 MB
  • 55. Low Light Image Enhancement MIRNet/1. Low Light Image Enhancement MIRNet.mp4 96.0 MB
  • 9. OpenCV Projects/10. Add and Remove Noise and Fix Contrast with Histogram Equalization.mp4 93.3 MB
  • 5. OpenCV - Haar Cascade Classifiers/2. Vehicle and Pedestrian Detection.mp4 90.3 MB
  • 31. Sign Language Detector TFODAPI EfficentDet/1. Sign Language Detector TFODAPI EfficentDet.mp4 89.3 MB
  • 9. OpenCV Projects/12. Facial Recognition.mp4 88.4 MB
  • 1. Introduction/1. Course Introduction.mp4 87.0 MB
  • 15. Improving Models and Advanced CNN Design/9. Training a Fashion Classifider (FNIST) with no Regularization using Keras.mp4 86.7 MB
  • 30. Mask Detector TFODAPI MobileNetV2_SSD/1. Mask Detector TFODAPI MobileNetV2_SSD.mp4 85.1 MB
  • 9. OpenCV Projects/8. Colorize Black and White Photos using a Caffe Model in OpenCV.mp4 84.9 MB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/3. Face Recognition Keras One Shot Learning and Friends.mp4 84.5 MB
  • 23. Autoencoders/2. Autoencoders in Keras.mp4 84.5 MB
  • 16. Visualizing What CNN's Learn/8. Grad-CAM Plus.mp4 84.3 MB
  • 3. OpenCV - Image Operations/10. Dilation, Erosion and Edge Detection.mp4 83.8 MB
  • 6. OpenCV - Image Analysis and Transformation/2. Histograms and K-Means Clustering for Dominant Colors.mp4 83.8 MB
  • 9. OpenCV Projects/5. YOLOv3 in OpenCV.mp4 83.4 MB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/1. Introduction to Deep Segmentation.mp4 82.0 MB
  • 46. Depth Estimation/1. Depth Estimation Project.mp4 80.5 MB
  • 44. Vision Transformers - ViTs/2. Vision Transformer in Detail with PyTorch.mp4 79.9 MB
  • 13. Building CNNs in TensorFlow with Keras/7. Saving and Loading and Visualising Results.mp4 79.2 MB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/2. Image Segmentation Keras UNET SegNet.mp4 76.6 MB
  • 25. Siamese Network/3. Siamese Networks in Keras.mp4 76.6 MB
  • 22. Google DeepStream and Neural Style Transfer/2. Google DeepDream in Keras.mp4 76.4 MB
  • 20. PyTorch Lightning/4. PyTorch Lightning Calls, Saving, Inference.mp4 75.1 MB
  • 39. Plant Doctor Detector YOLOv5/1. Plant Doctor Detector YOLOv5.mp4 74.6 MB
  • 7. OpenCV - Motion and Object Tracking/1. Motion Tracking with Mean Shift and CAMSHIFT.mp4 74.5 MB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/5. Detectron2 Mask R-CNN.mp4 74.3 MB
  • 12. Building CNNs in PyTorch/3. Inspect and Visualise Data.mp4 74.0 MB
  • 9. OpenCV Projects/4. Barcode, QR Generation and Reading.mp4 72.0 MB
  • 4. OpenCV - Image Segmentation/4. Counting Circles, Ellipses and Finding Waldo with Template Matching.mp4 71.8 MB
  • 3. OpenCV - Image Operations/3. Colour Spaces - RGB and HSV.mp4 71.6 MB
  • 14. Assessing Model Performance/1. Deep Learning Libraries PyTorch vs Keras Review.mp4 71.5 MB
  • 25. Siamese Network/4. Siamese Networks in PyTorch.mp4 71.2 MB
  • 14. Assessing Model Performance/3. Confusion Matrix and Classification Report.mp4 70.9 MB
  • 3. OpenCV - Image Operations/5. Transformations - Translations and Rotations.mp4 70.5 MB
  • 10. OpenCV - Working With Video/1. Using Your Webcam and Creating a Live Sketch of Yourself.mp4 69.8 MB
  • 3. OpenCV - Image Operations/7. Arithmetic and Bitwise Operations.mp4 69.4 MB
  • 6. OpenCV - Image Analysis and Transformation/6. Background and Foreground Subtraction.mp4 69.3 MB
  • 23. Autoencoders/3. Autoencoders in PyTorch.mp4 69.3 MB
  • 24. Generative Adversarial Networks (GANs)/6. PyTorch GANs.mp4 68.6 MB
  • 27. Object Detection/1. Object Detection.mp4 68.4 MB
  • 33. Mushroom Detector Detectron2/1. Mushroom Detector Detectron2.mp4 68.1 MB
  • 14. Assessing Model Performance/4. Keras Viewing Misclassifications.mp4 68.1 MB
  • 10. OpenCV - Working With Video/7. Importing YouTube Videos into OpenCV.mp4 68.0 MB
  • 13. Building CNNs in TensorFlow with Keras/4. Constructing the CNN.mp4 67.6 MB
  • 6. OpenCV - Image Analysis and Transformation/1. Perspective Transforms.mp4 67.6 MB
  • 15. Improving Models and Advanced CNN Design/11. Training a Fashion Classifider (FNIST) with no Regularization using PyTorch.mp4 67.3 MB
  • 20. PyTorch Lightning/5. Training on Multiple GPU, Profiling and TPUs.mp4 67.3 MB
  • 1. Introduction/2. Course Overview.mp4 66.9 MB
  • 20. PyTorch Lightning/2. Lightning Setup and Class.mp4 65.2 MB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/4. Mask-RCNN Tensorflow Matterport.mp4 64.7 MB
  • 53. Medical Project - X-Ray Pneumonia Prediction/1. X-Ray Pneumonia Prediction.mp4 64.4 MB
  • 54. Medical Project - 3D CT Scan Classification/1. 3D CT Scan Classification.mp4 63.2 MB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/3. PyTorch DeepLabV3.mp4 63.1 MB
  • 42. Tracking with DeepSORT/1. DeepSORT Introduction.mp4 62.4 MB
  • 51. Point Cloud Classification PointNet/1. Point Cloud Classification PointNet.mp4 62.4 MB
  • 32. Pothole Detector - TinyYOLOv4/1. Pothole Detector - TinyYOLOv4.mp4 62.4 MB
  • 11. Deep Learning in Computer Vision Introduction/22. Deep Learning Libraries Overview.mp4 61.9 MB
  • 9. OpenCV Projects/1. Tilt Shift Effects.mp4 61.9 MB
  • 3. OpenCV - Image Operations/8. Convolutions, Blurring and Sharpening Images.mp4 61.8 MB
  • 43. Deep Fakes/1. Creating a Deep Fake.mp4 61.5 MB
  • 45. BiT BigTransfer Classifier Keras/1. BiT BigTransfer Classifier Keras.mp4 61.5 MB
  • 37. Bloodcell Detector YOLOv5/1. Bloodcell Detector YOLOv5.mp4 61.4 MB
  • 42. Tracking with DeepSORT/2. DeepSORT with YOLOv5.mp4 61.2 MB
  • 22. Google DeepStream and Neural Style Transfer/3. Google DeepDream in PyTorch.mp4 61.2 MB
  • 22. Google DeepStream and Neural Style Transfer/6. Neural Style Transfer in PyTorch.mp4 60.7 MB
  • 11. Deep Learning in Computer Vision Introduction/21. Deep Learning History.mp4 60.3 MB
  • 35. Drone Maritime Detector R-CNN/1. Drone Maritime Detector R-CNN.mp4 59.6 MB
  • 49. Video Classification usign CNN+RNN/1. Video Classification usign CNN+RNN.mp4 59.5 MB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/2. Facial Similarity Keras VGGFace.mp4 59.4 MB
  • 4. OpenCV - Image Segmentation/3. Line, Circle and Blob Detection.mp4 59.3 MB
  • 47. Image Similarity using Metric Learning/1. Image Similarity using Metric Learning.mp4 58.7 MB
  • 21. Transfer Learning and Fine Tuning/2. Transfer Learning in PyTorch Lightning.mp4 58.6 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/6. Getting the Rank-N Accuracy in Keras.mp4 58.6 MB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/6. Train Mask R-CNN Shapes Dataset.mp4 57.6 MB
  • 56. Deploy your CV App using Flask RestFUL API & Web App/1. Flask RestFUL API.mp4 57.6 MB
  • 27. Object Detection/2. History of Object Detectors.mp4 55.4 MB
  • 3. OpenCV - Image Operations/2. Grayscaling Images.mp4 55.1 MB
  • 3. OpenCV - Image Operations/4. Drawing on Images.mp4 54.6 MB
  • 9. OpenCV Projects/7. SSDs in OpenCV.mp4 54.3 MB
  • 14. Assessing Model Performance/6. PyTorch Viewing Misclassifications.mp4 53.9 MB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/4. Face Recognition PyTorch FaceNet.mp4 53.8 MB
  • 22. Google DeepStream and Neural Style Transfer/4. Introduction to Neural Style Transfer.mp4 52.4 MB
  • 34. Website Region Detector YOLOv4 Darknet/1. Website Region Detector YOLOv4 Darknet.mp4 52.0 MB
  • 8. OpenCV - Facial Landmark Detection & Face Swaps/2. Face Swapping with Dlib.mp4 51.8 MB
  • 24. Generative Adversarial Networks (GANs)/3. Training GANs.mp4 51.7 MB
  • 12. Building CNNs in PyTorch/8. Saving Model and Displaying Results.mp4 51.7 MB
  • 50. Video Classification with Transformers/1. Video Classification with Transformers.mp4 51.6 MB
  • 7. OpenCV - Motion and Object Tracking/3. Simple Object Tracking by Color.mp4 51.0 MB
  • 44. Vision Transformers - ViTs/3. Vision Transformers in Keras.mp4 50.3 MB
  • 12. Building CNNs in PyTorch/1. Importing Required Libraries.mp4 50.0 MB
  • 57. OCR Captcha Cracker/1. OCR Captcha Cracker.mp4 48.6 MB
  • 10. OpenCV - Working With Video/6. Capturing Video using Screenshots.mp4 48.6 MB
  • 41. Body Pose Estimation/1. Body Pose Estimation.mp4 48.5 MB
  • 1. Introduction/3. What Makes Computer Vision Hard.mp4 48.4 MB
  • 27. Object Detection/4. Mean Average Precision.mp4 47.9 MB
  • 9. OpenCV Projects/2. GrabCut Algorithm for Background Removal.mp4 47.9 MB
  • 13. Building CNNs in TensorFlow with Keras/5. Training the Model.mp4 47.7 MB
  • 1. Introduction/4. What are Images.mp4 46.4 MB
  • 15. Improving Models and Advanced CNN Design/1. What is Overfitting and Generalisation.mp4 46.2 MB
  • 17. Advamced Convolutional Neural Networks/7. MobileNetV1 and V2.mp4 46.0 MB
  • 24. Generative Adversarial Networks (GANs)/1. Introduction to GANs.mp4 45.7 MB
  • 14. Assessing Model Performance/5. Keras - Confusion Matrix and Classification Report.mp4 45.5 MB
  • 6. OpenCV - Image Analysis and Transformation/5. Watershed Algorithm Marker-Dased Image Segmentation.mp4 45.4 MB
  • 36. Chess Piece YOLOv3/1. Chess Piece YOLOv3.mp4 44.7 MB
  • 6. OpenCV - Image Analysis and Transformation/3. Comparing Images MSE and Structual Similarity.mp4 44.1 MB
  • 10. OpenCV - Working With Video/4. Video Streams and CCTV - RTSP and IP.mp4 44.1 MB
  • 27. Object Detection/6. R-CNNs, Fast R-CNNs and Faster R-CNNs.mp4 43.2 MB
  • 11. Deep Learning in Computer Vision Introduction/19. Optimisers and Learning Rate Schedules.mp4 42.9 MB
  • 6. OpenCV - Image Analysis and Transformation/4. Filtering on Colour.mp4 42.9 MB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/6. Detectron2.mp4 42.6 MB
  • 22. Google DeepStream and Neural Style Transfer/1. Introduction to Google DeepDream Visualizations.mp4 41.8 MB
  • 9. OpenCV Projects/11. Detect Blur in Images.mp4 41.5 MB
  • 20. PyTorch Lightning/1. Introduction to PyTorch Lightning.mp4 40.1 MB
  • 8. OpenCV - Facial Landmark Detection & Face Swaps/1. Facial Landmark Detection with Dlib.mp4 39.4 MB
  • 56. Deploy your CV App using Flask RestFUL API & Web App/2. Flask Web App.mp4 39.1 MB
  • 4. OpenCV - Image Segmentation/5. Finding Corners.mp4 38.3 MB
  • 13. Building CNNs in TensorFlow with Keras/6. Plotting the Training Results.mp4 38.2 MB
  • 11. Deep Learning in Computer Vision Introduction/20. Deep Learning CNN Recap.mp4 38.2 MB
  • 10. OpenCV - Working With Video/5. Auto Reconnect to Video Streams.mp4 38.0 MB
  • 10. OpenCV - Working With Video/3. Saving or Recording Videos in OpenCV.mp4 37.5 MB
  • 16. Visualizing What CNN's Learn/2. Visualising Filter Activations.mp4 37.3 MB
  • 24. Generative Adversarial Networks (GANs)/8. AnimeGAN.mp4 36.5 MB
  • 10. OpenCV - Working With Video/2. Opening Video Files in OpenCV.mp4 35.6 MB
  • 11. Deep Learning in Computer Vision Introduction/2. Convolutions.mp4 35.5 MB
  • 13. Building CNNs in TensorFlow with Keras/3. Preprocessing Our Data.mp4 35.2 MB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/1. Introduction to YOLO.mp4 35.1 MB
  • 11. Deep Learning in Computer Vision Introduction/18. Gradient Descent.mp4 34.5 MB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/1. Face Recognition Overview.mp4 33.6 MB
  • 17. Advamced Convolutional Neural Networks/11. DenseNet.mp4 33.6 MB
  • 15. Improving Models and Advanced CNN Design/5. Data Augmentation.mp4 33.4 MB
  • 21. Transfer Learning and Fine Tuning/1. Transfer Learning Introduction.mp4 33.4 MB
  • 24. Generative Adversarial Networks (GANs)/9. ArcaneGAN.mp4 33.1 MB
  • 27. Object Detection/7. Single Shot Detectors (SSDs).mp4 32.4 MB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/5. EfficientDet.mp4 32.2 MB
  • 38. Hard Hat Detector EfficentDet/1. Hard Hat Detector EfficentDet.mp4 32.1 MB
  • 16. Visualizing What CNN's Learn/5. Class Maximization.mp4 31.6 MB
  • 12. Building CNNs in PyTorch/4. Data Loaders.mp4 31.4 MB
  • 12. Building CNNs in PyTorch/2. Transformation Pipeline.mp4 31.0 MB
  • 17. Advamced Convolutional Neural Networks/12. The ImageNet Dataset.mp4 31.0 MB
  • 13. Building CNNs in TensorFlow with Keras/2. View and Inspect Data.mp4 30.9 MB
  • 11. Deep Learning in Computer Vision Introduction/12. Putting Together Your Convolutional Neural Network.mp4 30.8 MB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/2. How YOLO Works.mp4 30.7 MB
  • 14. Assessing Model Performance/7. PyTorch - Confusion Matrix and Misclassifications.mp4 30.7 MB
  • 11. Deep Learning in Computer Vision Introduction/17. Backpropagation.mp4 30.4 MB
  • 24. Generative Adversarial Networks (GANs)/1.1 Slides - Generative Adverserial Networks.pdf 30.3 MB
  • 21. Transfer Learning and Fine Tuning/6. PyTorch Transfer Learning and Freezing Network Layers.mp4 30.2 MB
  • 25. Siamese Network/1. Introduction to Siamese Networks.mp4 30.2 MB
  • 9. OpenCV Projects/9. Inpainting to Restore Damaged Photos.mp4 29.9 MB
  • 11. Deep Learning in Computer Vision Introduction/15. Training a CNN.mp4 28.7 MB
  • 44. Vision Transformers - ViTs/1. Introduction to Vision Transformers.mp4 28.0 MB
  • 13. Building CNNs in TensorFlow with Keras/1. Loading Data.mp4 28.0 MB
  • 24. Generative Adversarial Networks (GANs)/2. How Do GANs Work.mp4 27.8 MB
  • 12. Building CNNs in PyTorch/9. Plot and Visualize Your Results.mp4 27.1 MB
  • 23. Autoencoders/1. Introduction to Autoencoders.mp4 26.6 MB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/3. Training YOLO.mp4 26.2 MB
  • 17. Advamced Convolutional Neural Networks/10. EfficientNet.mp4 26.2 MB
  • 11. Deep Learning in Computer Vision Introduction/16. Loss Functions.mp4 26.1 MB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/4. YOLO Evolution.mp4 25.4 MB
  • 11. Deep Learning in Computer Vision Introduction/3. Feature Detectors.mp4 25.0 MB
  • 15. Improving Models and Advanced CNN Design/7. Batch Normalization.mp4 25.0 MB
  • 11. Deep Learning in Computer Vision Introduction/13. Parameter Counts in CNNs.mp4 25.0 MB
  • 11. Deep Learning in Computer Vision Introduction/9. Pooling.mp4 24.6 MB
  • 17. Advamced Convolutional Neural Networks/8. InceptionV3.mp4 24.6 MB
  • 17. Advamced Convolutional Neural Networks/6. Why ResNets Work So Well.mp4 24.4 MB
  • 17. Advamced Convolutional Neural Networks/9. SqueezeNet.mp4 24.3 MB
  • 16. Visualizing What CNN's Learn/4. Maximizing Filters.mp4 24.2 MB
  • 17. Advamced Convolutional Neural Networks/4. VGG16 and VGG19.mp4 24.2 MB
  • 14. Assessing Model Performance/2. Assessing Model Performance.mp4 23.7 MB
  • 2. Download Code and Setup Colab/2. Setup - Download Code and Configure Colab.mp4 23.7 MB
  • 11. Deep Learning in Computer Vision Introduction/8. Activation Functions.mp4 22.8 MB
  • 11. Deep Learning in Computer Vision Introduction/14. Why CNNs Work So Well On Images.mp4 21.5 MB
  • 16. Visualizing What CNN's Learn/1. Visualizing CNN Filters or Feature Maps.mp4 21.5 MB
  • 27. Object Detection/5. Non Maximum Suppression.mp4 20.5 MB
  • 17. Advamced Convolutional Neural Networks/2. LeNet.mp4 19.6 MB
  • 17. Advamced Convolutional Neural Networks/5. ResNets.mp4 18.7 MB
  • 17. Advamced Convolutional Neural Networks/3. AlexNet.mp4 18.4 MB
  • 27. Object Detection/3. Intersection Over Union.mp4 18.3 MB
  • 11. Deep Learning in Computer Vision Introduction/7. Stride.mp4 18.0 MB
  • 11. Deep Learning in Computer Vision Introduction/4. 3D Convolutions and Color Images.mp4 17.4 MB
  • 19. Using Callbacks in Keras and PyTorch/1. What are Callbacks.mp4 17.0 MB
  • 11. Deep Learning in Computer Vision Introduction/1. Introduction to Convolution Neural Networks.mp4 16.6 MB
  • 15. Improving Models and Advanced CNN Design/4. L1 and L2 Regularization.mp4 16.4 MB
  • 16. Visualizing What CNN's Learn/7. Grad-CAM Visualize What Influences Your Model.mp4 15.6 MB
  • 12. Building CNNs in PyTorch/6. Optimisers and Loss Function.mp4 15.6 MB
  • 11. Deep Learning in Computer Vision Introduction/6. Padding.mp4 14.9 MB
  • 11. Deep Learning in Computer Vision Introduction/5. Kernel Size and Depth.mp4 14.3 MB
  • 25. Siamese Network/2. Training Siamese Networks.mp4 14.0 MB
  • 15. Improving Models and Advanced CNN Design/3. Drop Out.mp4 13.7 MB
  • 15. Improving Models and Advanced CNN Design/6. Early Stopping.mp4 13.6 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/4. The Top-N or Rank-N Accuracy Metric.mp4 13.0 MB
  • 15. Improving Models and Advanced CNN Design/8. When Do We Use Regularization.mp4 12.1 MB
  • 11. Deep Learning in Computer Vision Introduction/10. Fully Connected Layers.mp4 11.9 MB
  • 17. Advamced Convolutional Neural Networks/1. History and Evolution of Convolutional Neural Networks.mp4 9.6 MB
  • 11. Deep Learning in Computer Vision Introduction/11. Softmax.mp4 9.3 MB
  • 15. Improving Models and Advanced CNN Design/2. Introduction to Regularization.mp4 8.4 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/2. Loading Pre-trained Networks in PyTorch (ResNets, DenseNets, MobileNET, VGG19).srt 29.6 kB
  • 16. Visualizing What CNN's Learn/6. Filter and Class Maximization.srt 25.4 kB
  • 4. OpenCV - Image Segmentation/2. Moments, Sorting, Approximating and Matching Contours.srt 25.4 kB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/1. Implementing LeNet and AlexNet in Keras.srt 23.8 kB
  • 3. OpenCV - Image Operations/1. Getting Started with OpenCV4.srt 23.6 kB
  • 19. Using Callbacks in Keras and PyTorch/2. Cats vs Dogs Classifier using Callbacks in PyTorch.srt 23.4 kB
  • 22. Google DeepStream and Neural Style Transfer/5. Neural Style Transfer in Keras.srt 22.8 kB
  • 19. Using Callbacks in Keras and PyTorch/3. Cats vs Dogs Classifier using Callbacks in Keras.srt 22.8 kB
  • 16. Visualizing What CNN's Learn/3. Keras Filter Visualization and Activations.srt 22.6 kB
  • 21. Transfer Learning and Fine Tuning/5. PyTorch Fine Tuning.srt 22.2 kB
  • 4. OpenCV - Image Segmentation/1. Contours - Drawing, Hierarchy and Modes.srt 20.9 kB
  • 14. Assessing Model Performance/3. Confusion Matrix and Classification Report.srt 20.9 kB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/5. DeepFace - Age, Gender, Emotion, Ethnicity and Face Recognition.srt 20.5 kB
  • 11. Deep Learning in Computer Vision Introduction/21. Deep Learning History.srt 20.5 kB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/3. Loading Pre-trained Networks in Keras (ResNets, DenseNets, MobileNET, VGG19).srt 20.0 kB
  • 21. Transfer Learning and Fine Tuning/4. Keras Feature Extraction.srt 19.9 kB
  • 14. Assessing Model Performance/1. Deep Learning Libraries PyTorch vs Keras Review.srt 19.5 kB
  • 3. OpenCV - Image Operations/6. Scaling, Re-sizing, Interpolations and Cropping.srt 19.4 kB
  • 9. OpenCV Projects/3. OCR with PyTesseract and EasyOCR (Text Detection).srt 19.3 kB
  • 3. OpenCV - Image Operations/9. Thresholding, Binarization & Adaptive Thresholding.srt 19.2 kB
  • 12. Building CNNs in PyTorch/5. Building our Model.srt 18.8 kB
  • 15. Improving Models and Advanced CNN Design/12. Training a Fashion Classifider (FNIST) with Regularization using PyTorch.srt 18.4 kB
  • 12. Building CNNs in PyTorch/7. Training Your Model.srt 18.2 kB
  • 5. OpenCV - Haar Cascade Classifiers/1. Face and Eye Detection with Haar Cascade Classifiers.srt 18.2 kB
  • 29. Gun Detector - Scaled-YoloV4/1. Gun Detector - Scaled-YoloV4.srt 18.2 kB
  • 15. Improving Models and Advanced CNN Design/10. Training a Fashion Classifider (FNIST) with Regularization using Keras.srt 17.7 kB
  • 1. Introduction/1. Course Introduction.srt 17.6 kB
  • 21. Transfer Learning and Fine Tuning/3. Transfer Learning and Fine Tuning with Keras.srt 17.6 kB
  • 20. PyTorch Lightning/3. Auto Batch and Learning Rate Selection plus Tensorboards.srt 17.5 kB
  • 9. OpenCV Projects/6. Neural Style Transfer with OpenCV.srt 17.2 kB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/1. Introduction to Deep Segmentation.srt 17.1 kB
  • 24. Generative Adversarial Networks (GANs)/5. Keras DCGAN with MNIST.srt 16.8 kB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/5. Getting the Rank-N Accuracy in PyTorch.srt 16.8 kB
  • 1. Introduction/2. Course Overview.srt 16.6 kB
  • 13. Building CNNs in TensorFlow with Keras/7. Saving and Loading and Visualising Results.srt 16.3 kB
  • 11. Deep Learning in Computer Vision Introduction/22. Deep Learning Libraries Overview.srt 16.3 kB
  • 21. Transfer Learning and Fine Tuning/7. PyTorch Feature Extraction.srt 16.2 kB
  • 6. OpenCV - Image Analysis and Transformation/2. Histograms and K-Means Clustering for Dominant Colors.srt 16.0 kB
  • 7. OpenCV - Motion and Object Tracking/2. Object Tracking with Optical Flow.srt 15.9 kB
  • 17. Advamced Convolutional Neural Networks/7. MobileNetV1 and V2.srt 15.1 kB
  • 5. OpenCV - Haar Cascade Classifiers/2. Vehicle and Pedestrian Detection.srt 15.0 kB
  • 22. Google DeepStream and Neural Style Transfer/4. Introduction to Neural Style Transfer.srt 14.9 kB
  • 3. OpenCV - Image Operations/7. Arithmetic and Bitwise Operations.srt 14.9 kB
  • 9. OpenCV Projects/12. Facial Recognition.srt 14.8 kB
  • 3. OpenCV - Image Operations/4. Drawing on Images.srt 14.8 kB
  • 3. OpenCV - Image Operations/10. Dilation, Erosion and Edge Detection.srt 14.8 kB
  • 11. Deep Learning in Computer Vision Introduction/20. Deep Learning CNN Recap.srt 14.6 kB
  • 15. Improving Models and Advanced CNN Design/9. Training a Fashion Classifider (FNIST) with no Regularization using Keras.srt 14.6 kB
  • 48. Image Captioning with Keras/1. Image Captioning with Keras.srt 14.4 kB
  • 3. OpenCV - Image Operations/5. Transformations - Translations and Rotations.srt 14.3 kB
  • 9. OpenCV Projects/10. Add and Remove Noise and Fix Contrast with Histogram Equalization.srt 14.1 kB
  • 23. Autoencoders/2. Autoencoders in Keras.srt 14.0 kB
  • 24. Generative Adversarial Networks (GANs)/7. Super Resolution GAN.srt 13.9 kB
  • 24. Generative Adversarial Networks (GANs)/4. Use Cases for GANs.srt 13.7 kB
  • 52. Point Cloud Segmentation Using PointNet/1. Point Cloud Segmentation Using PointNet.srt 13.5 kB
  • 9. OpenCV Projects/4. Barcode, QR Generation and Reading.srt 13.4 kB
  • 27. Object Detection/1. Object Detection.srt 13.4 kB
  • 16. Visualizing What CNN's Learn/8. Grad-CAM Plus.srt 13.4 kB
  • 15. Improving Models and Advanced CNN Design/1. What is Overfitting and Generalisation.srt 13.3 kB
  • 11. Deep Learning in Computer Vision Introduction/2. Convolutions.srt 13.3 kB
  • 20. PyTorch Lightning/4. PyTorch Lightning Calls, Saving, Inference.srt 13.3 kB
  • 25. Siamese Network/3. Siamese Networks in Keras.srt 13.1 kB
  • 6. OpenCV - Image Analysis and Transformation/1. Perspective Transforms.srt 13.0 kB
  • 21. Transfer Learning and Fine Tuning/1. Transfer Learning Introduction.srt 13.0 kB
  • 12. Building CNNs in PyTorch/3. Inspect and Visualise Data.srt 12.9 kB
  • 9. OpenCV Projects/5. YOLOv3 in OpenCV.srt 12.8 kB
  • 42. Tracking with DeepSORT/1. DeepSORT Introduction.srt 12.7 kB
  • 3. OpenCV - Image Operations/3. Colour Spaces - RGB and HSV.srt 12.5 kB
  • 27. Object Detection/2. History of Object Detectors.srt 12.4 kB
  • 44. Vision Transformers - ViTs/2. Vision Transformer in Detail with PyTorch.srt 12.4 kB
  • 20. PyTorch Lightning/1. Introduction to PyTorch Lightning.srt 12.3 kB
  • 27. Object Detection/4. Mean Average Precision.srt 12.0 kB
  • 16. Visualizing What CNN's Learn/2. Visualising Filter Activations.srt 11.8 kB
  • 10. OpenCV - Working With Video/1. Using Your Webcam and Creating a Live Sketch of Yourself.srt 11.8 kB
  • 11. Deep Learning in Computer Vision Introduction/18. Gradient Descent.srt 11.8 kB
  • 9. OpenCV Projects/8. Colorize Black and White Photos using a Caffe Model in OpenCV.srt 11.8 kB
  • 14. Assessing Model Performance/4. Keras Viewing Misclassifications.srt 11.7 kB
  • 24. Generative Adversarial Networks (GANs)/6. PyTorch GANs.srt 11.7 kB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/2. Image Segmentation Keras UNET SegNet.srt 11.5 kB
  • 11. Deep Learning in Computer Vision Introduction/12. Putting Together Your Convolutional Neural Network.srt 11.5 kB
  • 23. Autoencoders/3. Autoencoders in PyTorch.srt 11.5 kB
  • 27. Object Detection/6. R-CNNs, Fast R-CNNs and Faster R-CNNs.srt 11.5 kB
  • 6. OpenCV - Image Analysis and Transformation/6. Background and Foreground Subtraction.srt 11.5 kB
  • 30. Mask Detector TFODAPI MobileNetV2_SSD/1. Mask Detector TFODAPI MobileNetV2_SSD.srt 11.4 kB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/3. Face Recognition Keras One Shot Learning and Friends.srt 11.3 kB
  • 24. Generative Adversarial Networks (GANs)/3. Training GANs.srt 11.2 kB
  • 1. Introduction/4. What are Images.srt 11.0 kB
  • 46. Depth Estimation/1. Depth Estimation Project.srt 11.0 kB
  • 55. Low Light Image Enhancement MIRNet/1. Low Light Image Enhancement MIRNet.srt 10.9 kB
  • 12. Building CNNs in PyTorch/8. Saving Model and Displaying Results.srt 10.9 kB
  • 7. OpenCV - Motion and Object Tracking/1. Motion Tracking with Mean Shift and CAMSHIFT.srt 10.8 kB
  • 15. Improving Models and Advanced CNN Design/11. Training a Fashion Classifider (FNIST) with no Regularization using PyTorch.srt 10.8 kB
  • 31. Sign Language Detector TFODAPI EfficentDet/1. Sign Language Detector TFODAPI EfficentDet.srt 10.8 kB
  • 22. Google DeepStream and Neural Style Transfer/2. Google DeepDream in Keras.srt 10.8 kB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/1. Face Recognition Overview.srt 10.8 kB
  • 23. Autoencoders/1. Introduction to Autoencoders.srt 10.7 kB
  • 12. Building CNNs in PyTorch/1. Importing Required Libraries.srt 10.7 kB
  • 17. Advamced Convolutional Neural Networks/11. DenseNet.srt 10.7 kB
  • 11. Deep Learning in Computer Vision Introduction/19. Optimisers and Learning Rate Schedules.srt 10.3 kB
  • 56. Deploy your CV App using Flask RestFUL API & Web App/1. Flask RestFUL API.srt 10.2 kB
  • 20. PyTorch Lightning/5. Training on Multiple GPU, Profiling and TPUs.srt 10.2 kB
  • 13. Building CNNs in TensorFlow with Keras/4. Constructing the CNN.srt 10.1 kB
  • 27. Object Detection/7. Single Shot Detectors (SSDs).srt 10.1 kB
  • 14. Assessing Model Performance/6. PyTorch Viewing Misclassifications.srt 10.1 kB
  • 11. Deep Learning in Computer Vision Introduction/16. Loss Functions.srt 10.1 kB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/6. Detectron2.srt 10.0 kB
  • 25. Siamese Network/4. Siamese Networks in PyTorch.srt 10.0 kB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/6. Getting the Rank-N Accuracy in Keras.srt 10.0 kB
  • 21. Transfer Learning and Fine Tuning/2. Transfer Learning in PyTorch Lightning.srt 9.9 kB
  • 10. OpenCV - Working With Video/7. Importing YouTube Videos into OpenCV.srt 9.8 kB
  • 11. Deep Learning in Computer Vision Introduction/15. Training a CNN.srt 9.8 kB
  • 20. PyTorch Lightning/2. Lightning Setup and Class.srt 9.8 kB
  • 3. OpenCV - Image Operations/2. Grayscaling Images.srt 9.6 kB
  • 1. Introduction/3. What Makes Computer Vision Hard.srt 9.6 kB
  • 39. Plant Doctor Detector YOLOv5/1. Plant Doctor Detector YOLOv5.srt 9.5 kB
  • 4. OpenCV - Image Segmentation/4. Counting Circles, Ellipses and Finding Waldo with Template Matching.srt 9.5 kB
  • 9. OpenCV Projects/2. GrabCut Algorithm for Background Removal.srt 9.4 kB
  • 45. BiT BigTransfer Classifier Keras/1. BiT BigTransfer Classifier Keras.srt 9.4 kB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/2. Facial Similarity Keras VGGFace.srt 9.4 kB
  • 3. OpenCV - Image Operations/8. Convolutions, Blurring and Sharpening Images.srt 9.3 kB
  • 4. OpenCV - Image Segmentation/3. Line, Circle and Blob Detection.srt 9.2 kB
  • 14. Assessing Model Performance/5. Keras - Confusion Matrix and Classification Report.srt 9.1 kB
  • 11. Deep Learning in Computer Vision Introduction/9. Pooling.srt 9.1 kB
  • 17. Advamced Convolutional Neural Networks/8. InceptionV3.srt 9.0 kB
  • 11. Deep Learning in Computer Vision Introduction/17. Backpropagation.srt 9.0 kB
  • 25. Siamese Network/1. Introduction to Siamese Networks.srt 8.9 kB
  • 9. OpenCV Projects/1. Tilt Shift Effects.srt 8.9 kB
  • 14. Assessing Model Performance/2. Assessing Model Performance.srt 8.9 kB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/1. Introduction to YOLO.srt 8.7 kB
  • 16. Visualizing What CNN's Learn/1. Visualizing CNN Filters or Feature Maps.srt 8.6 kB
  • 6. OpenCV - Image Analysis and Transformation/4. Filtering on Colour.srt 8.6 kB
  • 6. OpenCV - Image Analysis and Transformation/3. Comparing Images MSE and Structual Similarity.srt 8.6 kB
  • 51. Point Cloud Classification PointNet/1. Point Cloud Classification PointNet.srt 8.5 kB
  • 53. Medical Project - X-Ray Pneumonia Prediction/1. X-Ray Pneumonia Prediction.srt 8.4 kB
  • 6. OpenCV - Image Analysis and Transformation/5. Watershed Algorithm Marker-Dased Image Segmentation.srt 8.4 kB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/5. EfficientDet.srt 8.4 kB
  • 8. OpenCV - Facial Landmark Detection & Face Swaps/1. Facial Landmark Detection with Dlib.srt 8.4 kB
  • 11. Deep Learning in Computer Vision Introduction/13. Parameter Counts in CNNs.srt 8.4 kB
  • 8. OpenCV - Facial Landmark Detection & Face Swaps/2. Face Swapping with Dlib.srt 8.3 kB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/3. PyTorch DeepLabV3.srt 8.2 kB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/4. Face Recognition PyTorch FaceNet.srt 8.1 kB
  • 17. Advamced Convolutional Neural Networks/10. EfficientNet.srt 8.1 kB
  • 47. Image Similarity using Metric Learning/1. Image Similarity using Metric Learning.srt 8.1 kB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/4. YOLO Evolution.srt 8.1 kB
  • 54. Medical Project - 3D CT Scan Classification/1. 3D CT Scan Classification.srt 8.1 kB
  • 49. Video Classification usign CNN+RNN/1. Video Classification usign CNN+RNN.srt 8.0 kB
  • 11. Deep Learning in Computer Vision Introduction/7. Stride.srt 8.0 kB
  • 11. Deep Learning in Computer Vision Introduction/1. Introduction to Convolution Neural Networks.srt 7.9 kB
  • 17. Advamced Convolutional Neural Networks/12. The ImageNet Dataset.srt 7.9 kB
  • 11. Deep Learning in Computer Vision Introduction/8. Activation Functions.srt 7.9 kB
  • 32. Pothole Detector - TinyYOLOv4/1. Pothole Detector - TinyYOLOv4.srt 7.9 kB
  • 57. OCR Captcha Cracker/1. OCR Captcha Cracker.srt 7.8 kB
  • 16. Visualizing What CNN's Learn/5. Class Maximization.srt 7.8 kB
  • 7. OpenCV - Motion and Object Tracking/3. Simple Object Tracking by Color.srt 7.8 kB
  • 13. Building CNNs in TensorFlow with Keras/3. Preprocessing Our Data.srt 7.8 kB
  • 22. Google DeepStream and Neural Style Transfer/6. Neural Style Transfer in PyTorch.srt 7.7 kB
  • 35. Drone Maritime Detector R-CNN/1. Drone Maritime Detector R-CNN.srt 7.7 kB
  • 44. Vision Transformers - ViTs/3. Vision Transformers in Keras.srt 7.7 kB
  • 9. OpenCV Projects/11. Detect Blur in Images.srt 7.7 kB
  • 43. Deep Fakes/1. Creating a Deep Fake.srt 7.7 kB
  • 44. Vision Transformers - ViTs/1. Introduction to Vision Transformers.srt 7.7 kB
  • 12. Building CNNs in PyTorch/9. Plot and Visualize Your Results.srt 7.6 kB
  • 22. Google DeepStream and Neural Style Transfer/1. Introduction to Google DeepDream Visualizations.srt 7.5 kB
  • 33. Mushroom Detector Detectron2/1. Mushroom Detector Detectron2.srt 7.5 kB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/5. Detectron2 Mask R-CNN.srt 7.4 kB
  • 24. Generative Adversarial Networks (GANs)/2. How Do GANs Work.srt 7.4 kB
  • 10. OpenCV - Working With Video/6. Capturing Video using Screenshots.srt 7.3 kB
  • 17. Advamced Convolutional Neural Networks/5. ResNets.srt 7.2 kB
  • 17. Advamced Convolutional Neural Networks/4. VGG16 and VGG19.srt 7.2 kB
  • 36. Chess Piece YOLOv3/1. Chess Piece YOLOv3.srt 7.2 kB
  • 19. Using Callbacks in Keras and PyTorch/1. What are Callbacks.srt 7.2 kB
  • 12. Building CNNs in PyTorch/4. Data Loaders.srt 7.2 kB
  • 17. Advamced Convolutional Neural Networks/9. SqueezeNet.srt 7.0 kB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/6. Train Mask R-CNN Shapes Dataset.srt 7.0 kB
  • 34. Website Region Detector YOLOv4 Darknet/1. Website Region Detector YOLOv4 Darknet.srt 6.9 kB
  • 10. OpenCV - Working With Video/2. Opening Video Files in OpenCV.srt 6.9 kB
  • 15. Improving Models and Advanced CNN Design/7. Batch Normalization.srt 6.9 kB
  • 11. Deep Learning in Computer Vision Introduction/4. 3D Convolutions and Color Images.srt 6.8 kB
  • 37. Bloodcell Detector YOLOv5/1. Bloodcell Detector YOLOv5.srt 6.8 kB
  • 16. Visualizing What CNN's Learn/4. Maximizing Filters.srt 6.8 kB
  • 17. Advamced Convolutional Neural Networks/6. Why ResNets Work So Well.srt 6.8 kB
  • 9. OpenCV Projects/7. SSDs in OpenCV.srt 6.8 kB
  • 14. Assessing Model Performance/7. PyTorch - Confusion Matrix and Misclassifications.srt 6.7 kB
  • 15. Improving Models and Advanced CNN Design/5. Data Augmentation.srt 6.7 kB
  • 24. Generative Adversarial Networks (GANs)/1. Introduction to GANs.srt 6.7 kB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/3. Training YOLO.srt 6.7 kB
  • 4. OpenCV - Image Segmentation/5. Finding Corners.srt 6.7 kB
  • 13. Building CNNs in TensorFlow with Keras/2. View and Inspect Data.srt 6.6 kB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/4. Mask-RCNN Tensorflow Matterport.srt 6.6 kB
  • 50. Video Classification with Transformers/1. Video Classification with Transformers.srt 6.6 kB
  • 11. Deep Learning in Computer Vision Introduction/3. Feature Detectors.srt 6.6 kB
  • 10. OpenCV - Working With Video/4. Video Streams and CCTV - RTSP and IP.srt 6.6 kB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/2. How YOLO Works.srt 6.6 kB
  • 12. Building CNNs in PyTorch/2. Transformation Pipeline.srt 6.5 kB
  • 11. Deep Learning in Computer Vision Introduction/14. Why CNNs Work So Well On Images.srt 6.5 kB
  • 22. Google DeepStream and Neural Style Transfer/3. Google DeepDream in PyTorch.srt 6.5 kB
  • 13. Building CNNs in TensorFlow with Keras/5. Training the Model.srt 6.5 kB
  • 13. Building CNNs in TensorFlow with Keras/6. Plotting the Training Results.srt 6.3 kB
  • 56. Deploy your CV App using Flask RestFUL API & Web App/2. Flask Web App.srt 6.2 kB
  • 11. Deep Learning in Computer Vision Introduction/5. Kernel Size and Depth.srt 6.1 kB
  • 17. Advamced Convolutional Neural Networks/3. AlexNet.srt 6.1 kB
  • 9. OpenCV Projects/9. Inpainting to Restore Damaged Photos.srt 5.9 kB
  • 15. Improving Models and Advanced CNN Design/4. L1 and L2 Regularization.srt 5.9 kB
  • 42. Tracking with DeepSORT/2. DeepSORT with YOLOv5.srt 5.7 kB
  • 17. Advamced Convolutional Neural Networks/1. History and Evolution of Convolutional Neural Networks.srt 5.7 kB
  • 11. Deep Learning in Computer Vision Introduction/6. Padding.srt 5.7 kB
  • 24. Generative Adversarial Networks (GANs)/8. AnimeGAN.srt 5.5 kB
  • 38. Hard Hat Detector EfficentDet/1. Hard Hat Detector EfficentDet.srt 5.4 kB
  • 21. Transfer Learning and Fine Tuning/6. PyTorch Transfer Learning and Freezing Network Layers.srt 5.4 kB
  • 13. Building CNNs in TensorFlow with Keras/1. Loading Data.srt 5.3 kB
  • 15. Improving Models and Advanced CNN Design/6. Early Stopping.srt 5.2 kB
  • 25. Siamese Network/2. Training Siamese Networks.srt 4.9 kB
  • 15. Improving Models and Advanced CNN Design/3. Drop Out.srt 4.9 kB
  • 10. OpenCV - Working With Video/3. Saving or Recording Videos in OpenCV.srt 4.9 kB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/4. The Top-N or Rank-N Accuracy Metric.srt 4.7 kB
  • 41. Body Pose Estimation/1. Body Pose Estimation.srt 4.7 kB
  • 17. Advamced Convolutional Neural Networks/2. LeNet.srt 4.6 kB
  • 16. Visualizing What CNN's Learn/7. Grad-CAM Visualize What Influences Your Model.srt 4.6 kB
  • 10. OpenCV - Working With Video/5. Auto Reconnect to Video Streams.srt 4.5 kB
  • 27. Object Detection/5. Non Maximum Suppression.srt 4.5 kB
  • 27. Object Detection/3. Intersection Over Union.srt 4.4 kB
  • 2. Download Code and Setup Colab/2. Setup - Download Code and Configure Colab.srt 4.3 kB
  • 11. Deep Learning in Computer Vision Introduction/10. Fully Connected Layers.srt 4.3 kB
  • 11. Deep Learning in Computer Vision Introduction/11. Softmax.srt 4.0 kB
  • 24. Generative Adversarial Networks (GANs)/9. ArcaneGAN.srt 3.8 kB
  • 15. Improving Models and Advanced CNN Design/8. When Do We Use Regularization.srt 3.6 kB
  • 12. Building CNNs in PyTorch/6. Optimisers and Loss Function.srt 3.3 kB
  • 15. Improving Models and Advanced CNN Design/2. Introduction to Regularization.srt 2.9 kB
  • 2. Download Code and Setup Colab/1. Download Course Resources.html 804 Bytes
  • 0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
  • 23. Autoencoders/0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
  • 6. OpenCV - Image Analysis and Transformation/0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
  • 0. Websites you may like/[CourseClub.Me].url 122 Bytes
  • 23. Autoencoders/0. Websites you may like/[CourseClub.Me].url 122 Bytes
  • 6. OpenCV - Image Analysis and Transformation/0. Websites you may like/[CourseClub.Me].url 122 Bytes
  • 0. Websites you may like/[GigaCourse.Com].url 49 Bytes
  • 23. Autoencoders/0. Websites you may like/[GigaCourse.Com].url 49 Bytes
  • 6. OpenCV - Image Analysis and Transformation/0. Websites you may like/[GigaCourse.Com].url 49 Bytes

随机展示

相关说明

本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！