Udemy - Modern Computer Vision & Deep Learning with Python & PyTorch (12.2024)
File List
- 09. Overview of YOLO Family for Object Detection/01. Overview of YOLO Family.mp4 264.9 MB
- 05. 1. Image Classification Task of Computer Vision/02. Image Classification with Deep Convolutional Neural Networks using Python.mp4 229.9 MB
- 20. Implementation, Optimization and Training Of Segmentation Models/01. Implement Segmentation Models (UNet, PSPNet, DeepLab, PAN, and UNet++).mp4 197.7 MB
- 07. Transfer Learning for Image Classification/assets/Classification-Dataset.zip 176.3 MB
- 25. Training, Evaluating and Visualizing Instance Segmentation on Custom Dataset/02. Train, Evaluate Instance Segmentation Model & Visualizing Results on Custom Data.mp4 174.0 MB
- 04. Computer Vision and Deep Convolutional Neural Networks/03. Coding Convolutional Neural Network Architecture from Scratch.mp4 163.1 MB
- 12. Detectron2 for Ojbect Detection/01. Detectron2 for Ojbect Detection with PyTorch.mp4 160.4 MB
- 13. Training, Evaluating and Visualizing Object Detection on Custom Dataset/03. Train, Evaluate Object Detection Models & Visualizing Results on Custom Dataset.mp4 153.4 MB
- 03. Deep Learning for Computer Vision/01. Basics of Deep Learning for Computer Vision.mp4 150.8 MB
- 11. Overview of RCNN Family for Object Detection/01. Overview of RCNN Family for Object Detection.mp4 147.3 MB
- 15. 3. Semantic Segmentation Task Of Computer Vision/02. Semantic Segmentation Real-World Applications.mp4 144.4 MB
- 12. Detectron2 for Ojbect Detection/02. Perform Object Detection using Detectron2 Pretrained Models.mp4 137.0 MB
- 04. Computer Vision and Deep Convolutional Neural Networks/06. Calculate Accuracy, Precision, Recall and Visualize Confusion Matrix.mp4 118.2 MB
- 21. Test Models and Visualize Segmentation Results/01. Test Models and Calculate IOU,Pixel Accuracy,Fscore.mp4 113.4 MB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/04. Data Loading with PyTorch Customized Dataset Class.mp4 109.6 MB
- 02. What is Computer Vision & its Applications/01. Introduction to Computer Vision and its Real-world Applications.mp4 108.7 MB
- 10. Video Object Detection in Real-time/04. Testing YOLO8 on Videos and Images.mp4 107.5 MB
- 13. Training, Evaluating and Visualizing Object Detection on Custom Dataset/01. Custom Dataset for Object Detection.mp4 88.4 MB
- 25. Training, Evaluating and Visualizing Instance Segmentation on Custom Dataset/01. Custom Dataset for Instance Segmentation.mp4 86.1 MB
- 21. Test Models and Visualize Segmentation Results/03. Visualize Segmentation Results and Generate RGB Segmented Map.mp4 86.0 MB
- 10. Video Object Detection in Real-time/01. Vehicles Detection Custom Dataset.mp4 69.4 MB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/06. Data Augmentation using Albumentations with Different Transformations.mp4 64.3 MB
- 18. Performance Metrics (IOU) For Segmentation Models Evaluation/01. Performance Metrics (IOU, Pixel Accuracy, Precision, Recall, Fscore).mp4 61.0 MB
- 10. Video Object Detection in Real-time/02. Setting HyperParameters for YOLO8.mp4 58.5 MB
- 27. Video Instance Segmentation/05. Training Video Instance Segmentation Model.mp4 57.3 MB
- 27. Video Instance Segmentation/02. YOLO8 for Video Instance Segmentation.mp4 55.9 MB
- 10. Video Object Detection in Real-time/05. Calculate Performance Metrics (Precision, Recall, Mean Average Precision mAP).mp4 54.4 MB
- 04. Computer Vision and Deep Convolutional Neural Networks/01. Computer Vision using Convolutional Neural Networks (CNN).mp4 53.4 MB
- 20. Implementation, Optimization and Training Of Segmentation Models/05. Training of Segmentation Models.mp4 52.8 MB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/02. Data Annotations Tool for Semantic Segmentation.mp4 50.4 MB
- 07. Transfer Learning for Image Classification/04. FineTuning Deep ResNet Model.mp4 49.0 MB
- 27. Video Instance Segmentation/07. Testing Segmentation Model on Videos.mp4 42.7 MB
- 10. Video Object Detection in Real-time/03. Training YOLO8 on Vehicles Dataset.mp4 42.5 MB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/01. Datasets for Semantic Segmentation.mp4 41.4 MB
- 06. Pretrained Models for Single and Multi-Label Image Classification/07. Multi-Label Image Classification using Deep Learning Models.mp4 38.3 MB
- 10. Video Object Detection in Real-time/assets/VehiclesDetection-Dataset.zip 38.1 MB
- 27. Video Instance Segmentation/assets/TestVideos.zip 37.8 MB
- 09. Overview of YOLO Family for Object Detection/03. YOLOv8 and its Architecture.mp4 37.5 MB
- 04. Computer Vision and Deep Convolutional Neural Networks/05. Training Convolutional Neural Network from Scratch.mp4 36.9 MB
- 13. Training, Evaluating and Visualizing Object Detection on Custom Dataset/assets/balloon.zip 36.9 MB
- 14. Complete Code and Custom Dataset for Object Detection/assets/balloon.zip 36.9 MB
- 26. Complete Code and Custom Dataset for Instance Segmentation/assets/balloon.zip 36.9 MB
- 07. Transfer Learning for Image Classification/08. Model Optimization, Training and Results Visualization.mp4 35.9 MB
- 27. Video Instance Segmentation/01. Intro to Video Instance Segmentation.mp4 35.3 MB
- 19. Encoders and Decoders For Segmentation In PyTorch/01. Transfer Learning And Pretrained Deep Resnet Architecture.mp4 35.2 MB
- 07. Transfer Learning for Image Classification/02. Dataset, Data Augmentation, and Dataloaders.mp4 35.0 MB
- 04. Computer Vision and Deep Convolutional Neural Networks/04. Convolutional Neural Networks HyperParameters Optimization.mp4 34.9 MB
- 15. 3. Semantic Segmentation Task Of Computer Vision/01. Semantic Segmentation Task Of Computer Vision with Pytorch and Python.mp4 33.0 MB
- 10. Video Object Detection in Real-time/06. Export and Deploy the Model.mp4 31.6 MB
- 04. Computer Vision and Deep Convolutional Neural Networks/02. Setting-up Google Colab for Writing Python Code.mp4 31.4 MB
- 06. Pretrained Models for Single and Multi-Label Image Classification/05. Single-Label Image Classification using ResNet and AlexNet PreTrained Models.mp4 31.0 MB
- 23. 4. Instance Segmentation Task of Computer Vision/01. Instance Segmentation Task of Computer Vision with Python.mp4 30.9 MB
- 27. Video Instance Segmentation/03. Custom Dataset for Instance Segmentation.mp4 28.9 MB
- 08. 2. Object Detection Task Of Computer Vision/01. Object Detection Task Of Computer Vision with Python.mp4 28.0 MB
- 27. Video Instance Segmentation/06. Testing Segmentation Model on Images.mp4 27.6 MB
- 19. Encoders and Decoders For Segmentation In PyTorch/03. Decoders for Segmentation in PyTorch Liberary.mp4 26.7 MB
- 07. Transfer Learning for Image Classification/05. HyperParameteres Optimization for Model.mp4 26.5 MB
- 07. Transfer Learning for Image Classification/01. Introduction to Transfer Learning.mp4 25.5 MB
- 01. Introduction to Course/01. Introduction to Computer Vision Course.mp4 24.6 MB
- 10. Video Object Detection in Real-time/assets/TestVideo.zip 24.5 MB
- 22. Complete Code and Dataset for Semantic Segmentation/01. Final Code Review.mp4 24.4 MB
- 16. Deep Learning Architectures For Segmentation (UNet, PSPNet, PAN)/01. Pyramid Scene Parsing Network (PSPNet) For Segmentation.mp4 24.4 MB
- 16. Deep Learning Architectures For Segmentation (UNet, PSPNet, PAN)/04. Multi-Task Contextual Network (MTCNet).mp4 23.8 MB
- 27. Video Instance Segmentation/04. Setting-up Hyper Parameters for Model.mp4 23.5 MB
- 06. Pretrained Models for Single and Multi-Label Image Classification/01. Introduction to Pretrained Models.mp4 21.3 MB
- 06. Pretrained Models for Single and Multi-Label Image Classification/02. Deep Learning ResNet and AlexNet Architectures.mp4 21.0 MB
- 19. Encoders and Decoders For Segmentation In PyTorch/02. Encoders for Segmentation with PyTorch Liberary.mp4 19.9 MB
- 06. Pretrained Models for Single and Multi-Label Image Classification/03. Access Data from Google Drive to Colab.mp4 19.6 MB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/assets/TrayDataset-for-Segmentation.zip 18.6 MB
- 22. Complete Code and Dataset for Semantic Segmentation/assets/Lecture-3-TrayDataset-for-Segmentation.zip 18.6 MB
- 14. Complete Code and Custom Dataset for Object Detection/assets/Python-and-PyTorch-Code.zip 18.0 MB
- 27. Video Instance Segmentation/08. Deploy Video Segmentation Model.mp4 17.9 MB
- 07. Transfer Learning for Image Classification/07. Fixed Feature Extractraction using ResNet.mp4 17.8 MB
- 16. Deep Learning Architectures For Segmentation (UNet, PSPNet, PAN)/03. Pyramid Attention Network (PAN).mp4 17.7 MB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/08. Learn To Implement Data Loaders In Pytorch.mp4 17.0 MB
- 24. Mask RCNN for Instance Segmentation/01. Mask RCNN for Instance Segmentation.mp4 16.8 MB
- 06. Pretrained Models for Single and Multi-Label Image Classification/04. Data Preprocessing for Image Classification.mp4 16.5 MB
- 20. Implementation, Optimization and Training Of Segmentation Models/03. Learn To Optimize Hyperparameters For Segmentation Models.mp4 16.5 MB
- 13. Training, Evaluating and Visualizing Object Detection on Custom Dataset/assets/Object-Detection-On-Custom-Dataset.ipynb 15.7 MB
- 07. Transfer Learning for Image Classification/06. Training Deep ResNet Model.mp4 13.5 MB
- 12. Detectron2 for Ojbect Detection/assets/Object-Detection-with-Detctron2.ipynb 13.3 MB
- 02. What is Computer Vision & its Applications/02. Major Computer Vision Tasks.mp4 11.3 MB
- 16. Deep Learning Architectures For Segmentation (UNet, PSPNet, PAN)/02. UNet Architecture For Segmentation.mp4 8.7 MB
- 05. 1. Image Classification Task of Computer Vision/01. Image Classification Task of Computer Vision with Pytoch and Python.mp4 6.8 MB
- 26. Complete Code and Custom Dataset for Instance Segmentation/assets/Instance-Segmentation-on-Custom-Dataset.zip 6.4 MB
- 09. Overview of YOLO Family for Object Detection/assets/YOLO-You-Only-Look-Once.pdf 5.1 MB
- 09. Overview of YOLO Family for Object Detection/assets/YOLO2.pdf 5.0 MB
- 09. Overview of YOLO Family for Object Detection/assets/YOLO4.pdf 3.8 MB
- 27. Video Instance Segmentation/assets/VehicleSegmentation.zip 3.2 MB
- 09. Overview of YOLO Family for Object Detection/assets/YOLO3.pdf 2.3 MB
- 09. Overview of YOLO Family for Object Detection/assets/YOLO7.pdf 2.2 MB
- 09. Overview of YOLO Family for Object Detection/assets/YOLO4-CSPNet.pdf 1.4 MB
- 09. Overview of YOLO Family for Object Detection/assets/YOLO6.pdf 1.0 MB
- 10. Video Object Detection in Real-time/assets/VehiclesDetection.ipynb 1.0 MB
- 06. Pretrained Models for Single and Multi-Label Image Classification/assets/Lecture-2-Resources-Single-Label-Classification.zip 995.2 KB
- 22. Complete Code and Dataset for Semantic Segmentation/assets/Lecture-2-Final-Code.zip 938.9 KB
- 09. Overview of YOLO Family for Object Detection/assets/YOLO5-EfficientNet.pdf 752.2 KB
- 09. Overview of YOLO Family for Object Detection/assets/YOLO5.pdf 734.0 KB
- 27. Video Instance Segmentation/assets/Code-Instance-Segmentation.zip 363.4 KB
- 05. 1. Image Classification Task of Computer Vision/assets/Image-Classification-with-Deep-CNN.zip 240.7 KB
- 06. Pretrained Models for Single and Multi-Label Image Classification/assets/Lecture-2-Resources-Multi-Label-Classification.zip 227.2 KB
- 04. Computer Vision and Deep Convolutional Neural Networks/assets/Resources-Code-for-Convolutional-Neural-Networks-from-Scratch-with-Python.zip 179.6 KB
- 07. Transfer Learning for Image Classification/assets/Code-for-Transfer-Learning-by-FineTuning-and-Model-Feature-Extractor.zip 120.5 KB
- 09. Overview of YOLO Family for Object Detection/01. Overview of YOLO Family.vtt 41.2 KB
- 04. Computer Vision and Deep Convolutional Neural Networks/03. Coding Convolutional Neural Network Architecture from Scratch.vtt 35.1 KB
- 11. Overview of RCNN Family for Object Detection/01. Overview of RCNN Family for Object Detection.vtt 30.5 KB
- 05. 1. Image Classification Task of Computer Vision/02. Image Classification with Deep Convolutional Neural Networks using Python.vtt 29.5 KB
- 03. Deep Learning for Computer Vision/01. Basics of Deep Learning for Computer Vision.vtt 27.7 KB
- 25. Training, Evaluating and Visualizing Instance Segmentation on Custom Dataset/02. Train, Evaluate Instance Segmentation Model & Visualizing Results on Custom Data.vtt 23.1 KB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/04. Data Loading with PyTorch Customized Dataset Class.vtt 22.9 KB
- 12. Detectron2 for Ojbect Detection/01. Detectron2 for Ojbect Detection with PyTorch.vtt 22.7 KB
- 20. Implementation, Optimization and Training Of Segmentation Models/01. Implement Segmentation Models (UNet, PSPNet, DeepLab, PAN, and UNet++).vtt 20.3 KB
- 04. Computer Vision and Deep Convolutional Neural Networks/06. Calculate Accuracy, Precision, Recall and Visualize Confusion Matrix.vtt 18.8 KB
- 18. Performance Metrics (IOU) For Segmentation Models Evaluation/02. Code (Python and PyTorch).html 18.3 KB
- 27. Video Instance Segmentation/02. YOLO8 for Video Instance Segmentation.vtt 16.7 KB
- 09. Overview of YOLO Family for Object Detection/03. YOLOv8 and its Architecture.vtt 16.7 KB
- 13. Training, Evaluating and Visualizing Object Detection on Custom Dataset/03. Train, Evaluate Object Detection Models & Visualizing Results on Custom Dataset.vtt 16.4 KB
- 21. Test Models and Visualize Segmentation Results/03. Visualize Segmentation Results and Generate RGB Segmented Map.vtt 16.3 KB
- 25. Training, Evaluating and Visualizing Instance Segmentation on Custom Dataset/01. Custom Dataset for Instance Segmentation.vtt 15.8 KB
- 13. Training, Evaluating and Visualizing Object Detection on Custom Dataset/01. Custom Dataset for Object Detection.vtt 15.7 KB
- 21. Test Models and Visualize Segmentation Results/01. Test Models and Calculate IOU,Pixel Accuracy,Fscore.vtt 15.5 KB
- 15. 3. Semantic Segmentation Task Of Computer Vision/02. Semantic Segmentation Real-World Applications.vtt 14.0 KB
- 02. What is Computer Vision & its Applications/01. Introduction to Computer Vision and its Real-world Applications.vtt 13.3 KB
- 19. Encoders and Decoders For Segmentation In PyTorch/02. Encoders for Segmentation with PyTorch Liberary.vtt 13.1 KB
- 18. Performance Metrics (IOU) For Segmentation Models Evaluation/01. Performance Metrics (IOU, Pixel Accuracy, Precision, Recall, Fscore).vtt 13.1 KB
- 19. Encoders and Decoders For Segmentation In PyTorch/03. Decoders for Segmentation in PyTorch Liberary.vtt 12.7 KB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/06. Data Augmentation using Albumentations with Different Transformations.vtt 12.7 KB
- 12. Detectron2 for Ojbect Detection/02. Perform Object Detection using Detectron2 Pretrained Models.vtt 12.5 KB
- 04. Computer Vision and Deep Convolutional Neural Networks/04. Convolutional Neural Networks HyperParameters Optimization.vtt 12.2 KB
- 04. Computer Vision and Deep Convolutional Neural Networks/01. Computer Vision using Convolutional Neural Networks (CNN).vtt 11.6 KB
- 20. Implementation, Optimization and Training Of Segmentation Models/05. Training of Segmentation Models.vtt 11.6 KB
- 20. Implementation, Optimization and Training Of Segmentation Models/06. Model Training Code (Python And PyTorch).html 11.3 KB
- 21. Test Models and Visualize Segmentation Results/02. Test Models and Calculate Performance Scores (Python Code).html 10.9 KB
- 20. Implementation, Optimization and Training Of Segmentation Models/03. Learn To Optimize Hyperparameters For Segmentation Models.vtt 10.4 KB
- 19. Encoders and Decoders For Segmentation In PyTorch/01. Transfer Learning And Pretrained Deep Resnet Architecture.vtt 10.4 KB
- 08. 2. Object Detection Task Of Computer Vision/01. Object Detection Task Of Computer Vision with Python.vtt 9.2 KB
- 13. Training, Evaluating and Visualizing Object Detection on Custom Dataset/04. Python and PyTorch Code.html 9.2 KB
- 06. Pretrained Models for Single and Multi-Label Image Classification/05. Single-Label Image Classification using ResNet and AlexNet PreTrained Models.vtt 9.1 KB
- 07. Transfer Learning for Image Classification/02. Dataset, Data Augmentation, and Dataloaders.vtt 9.1 KB
- 07. Transfer Learning for Image Classification/04. FineTuning Deep ResNet Model.vtt 8.5 KB
- 10. Video Object Detection in Real-time/05. Calculate Performance Metrics (Precision, Recall, Mean Average Precision mAP).vtt 8.5 KB
- 10. Video Object Detection in Real-time/04. Testing YOLO8 on Videos and Images.vtt 8.3 KB
- 10. Video Object Detection in Real-time/02. Setting HyperParameters for YOLO8.vtt 8.2 KB
- 07. Transfer Learning for Image Classification/01. Introduction to Transfer Learning.vtt 7.9 KB
- 06. Pretrained Models for Single and Multi-Label Image Classification/07. Multi-Label Image Classification using Deep Learning Models.vtt 7.9 KB
- 27. Video Instance Segmentation/04. Setting-up Hyper Parameters for Model.vtt 7.9 KB
- 04. Computer Vision and Deep Convolutional Neural Networks/02. Setting-up Google Colab for Writing Python Code.vtt 7.8 KB
- 07. Transfer Learning for Image Classification/08. Model Optimization, Training and Results Visualization.vtt 7.8 KB
- 07. Transfer Learning for Image Classification/05. HyperParameteres Optimization for Model.vtt 7.7 KB
- 15. 3. Semantic Segmentation Task Of Computer Vision/01. Semantic Segmentation Task Of Computer Vision with Pytorch and Python.vtt 7.3 KB
- 10. Video Object Detection in Real-time/03. Training YOLO8 on Vehicles Dataset.vtt 7.2 KB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/01. Datasets for Semantic Segmentation.vtt 7.2 KB
- 27. Video Instance Segmentation/05. Training Video Instance Segmentation Model.vtt 7.1 KB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/02. Data Annotations Tool for Semantic Segmentation.vtt 6.9 KB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/05. Data Loading for Segmentation with Python and PyTorch Code.html 6.8 KB
- 10. Video Object Detection in Real-time/01. Vehicles Detection Custom Dataset.vtt 6.7 KB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/08. Learn To Implement Data Loaders In Pytorch.vtt 6.4 KB
- 27. Video Instance Segmentation/03. Custom Dataset for Instance Segmentation.vtt 6.4 KB
- 27. Video Instance Segmentation/07. Testing Segmentation Model on Videos.vtt 6.2 KB
- 23. 4. Instance Segmentation Task of Computer Vision/01. Instance Segmentation Task of Computer Vision with Python.vtt 6.2 KB
- 16. Deep Learning Architectures For Segmentation (UNet, PSPNet, PAN)/01. Pyramid Scene Parsing Network (PSPNet) For Segmentation.vtt 5.8 KB
- 06. Pretrained Models for Single and Multi-Label Image Classification/01. Introduction to Pretrained Models.vtt 5.7 KB
- 07. Transfer Learning for Image Classification/07. Fixed Feature Extractraction using ResNet.vtt 5.7 KB
- 16. Deep Learning Architectures For Segmentation (UNet, PSPNet, PAN)/04. Multi-Task Contextual Network (MTCNet).vtt 5.5 KB
- 27. Video Instance Segmentation/01. Intro to Video Instance Segmentation.vtt 5.4 KB
- 24. Mask RCNN for Instance Segmentation/01. Mask RCNN for Instance Segmentation.vtt 5.3 KB
- 12. Detectron2 for Ojbect Detection/03. Python and PyTorch Code.html 5.2 KB
- 06. Pretrained Models for Single and Multi-Label Image Classification/02. Deep Learning ResNet and AlexNet Architectures.vtt 5.0 KB
- 06. Pretrained Models for Single and Multi-Label Image Classification/04. Data Preprocessing for Image Classification.vtt 5.0 KB
- 16. Deep Learning Architectures For Segmentation (UNet, PSPNet, PAN)/02. UNet Architecture For Segmentation.vtt 4.8 KB
- 27. Video Instance Segmentation/06. Testing Segmentation Model on Images.vtt 4.6 KB
- 28. Bonus Lecture Video Object Detection and Video Segmentation with Python/01. Bonus Lecture Video Object Detection and Video Segmentation with Python.html 4.5 KB
- 16. Deep Learning Architectures For Segmentation (UNet, PSPNet, PAN)/03. Pyramid Attention Network (PAN).vtt 4.4 KB
- 07. Transfer Learning for Image Classification/06. Training Deep ResNet Model.vtt 4.2 KB
- 22. Complete Code and Dataset for Semantic Segmentation/01. Final Code Review.vtt 4.0 KB
- 01. Introduction to Course/01. Introduction to Computer Vision Course.vtt 3.9 KB
- 02. What is Computer Vision & its Applications/02. Major Computer Vision Tasks.vtt 3.7 KB
- 04. Computer Vision and Deep Convolutional Neural Networks/05. Training Convolutional Neural Network from Scratch.vtt 3.5 KB
- 10. Video Object Detection in Real-time/06. Export and Deploy the Model.vtt 3.4 KB
- 06. Pretrained Models for Single and Multi-Label Image Classification/03. Access Data from Google Drive to Colab.vtt 3.4 KB
- 27. Video Instance Segmentation/08. Deploy Video Segmentation Model.vtt 3.3 KB
- 05. 1. Image Classification Task of Computer Vision/01. Image Classification Task of Computer Vision with Pytoch and Python.vtt 3.2 KB
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/07. Augmentation Python Code.html 2.7 KB
- 21. Test Models and Visualize Segmentation Results/04. Segmentation Results Visualization (Python Code).html 2.7 KB
- 20. Implementation, Optimization and Training Of Segmentation Models/02. Segmentation Models Code with Python.html 1.0 KB
- 20. Implementation, Optimization and Training Of Segmentation Models/04. Model Optimaztion Code (Python And PyTorch).html 292 bytes
- 05. 1. Image Classification Task of Computer Vision/03. Resources Code for Image Classification with Deep CNN from Scratch.html 166 bytes
- 04. Computer Vision and Deep Convolutional Neural Networks/07. Resources Complete Code for CNN from Scratch with Python and Pytorch.html 141 bytes
- 27. Video Instance Segmentation/09. Resources Video Segmentation Complete Code and Dataset.html 120 bytes
- 17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/03. Dataset for Semantic Segmentation.html 119 bytes
- 06. Pretrained Models for Single and Multi-Label Image Classification/06. Single Label Classification Python and Pytorch Code.html 114 bytes
- 22. Complete Code and Dataset for Semantic Segmentation/02. Complete Code and Dataset is Attached.html 106 bytes
- 06. Pretrained Models for Single and Multi-Label Image Classification/08. Multi-Label Classification Python and PyTorch Code.html 101 bytes
- 26. Complete Code and Custom Dataset for Instance Segmentation/01. Resources Complete Code and Custom Dataset for Instance Segmentation.html 90 bytes
- 10. Video Object Detection in Real-time/07. Resources Videos Vehicles Detection Complete Code and Dataset.html 88 bytes
- 07. Transfer Learning for Image Classification/09. Complete Python Code for Transfer Learning and Dataset.html 77 bytes
- 14. Complete Code and Custom Dataset for Object Detection/01. Resources Code and Custom Dataset for Object Detection.html 76 bytes
- 07. Transfer Learning for Image Classification/03. Dataset for Classification.html 69 bytes
- 09. Overview of YOLO Family for Object Detection/02. YOLO Family Research Papers.html 66 bytes
- 13. Training, Evaluating and Visualizing Object Detection on Custom Dataset/02. Dataset for Object Detection.html 56 bytes
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