Applied Computer Vision Object Detection and Recognition

سرفصل های دوره

01 Introduction Fundamental Concepts in Image Recognition

001 Course Introduction

002 Fundamental Concepts in Image Recognition

003 Environment setup.html

004 Summary.html

004 code-repo.zip

external-links.txt

02 Recap of CNNs

001 Convolution in 1D

002 Convolution in 2D

003 Pooling and subsampling

004 Activation functions

006 Building a basic CNN

007 Backpropagation

008 Dropout

009 Notebooks description part 1 PyTorch Tutorials.html

010 Notebooks description part 2 FiftyOne Tutorials.html

010 section2-conv-nets-fiftyone-tutorial-part1.ipynb.zip

010 section2-conv-nets-fiftyone-tutorial-part2.ipynb.zip

010 section2-conv-nets-fiftyone-tutorial-part3.ipynb.zip

010 section2-conv-nets-pytorch-tutorial-part1.ipynb.zip

010 section2-conv-nets-pytorch-tutorial-part2.ipynb.zip

external-links.txt

03 Image Classification

001 Introduction to Image Classification

003 Build an Image Classifier

004 ResNet Family of Models

006 Torchvision Models

007 Performance Metrics for Image Classification

009 Notebooks Description.html

009 section3-classification-part1-prepare-data.ipynb.zip

009 section3-classification-part2-build-classifier.ipynb.zip

external-links.txt

04 Object Detection

001 Introduction to Object Detection

002 Object Detection Models

003 Twostage Object Detectors RCNN part1

004 Twostage Object Detectors RCNN part2

005 Twostage Object Detectors RCNN part3

006 Twostage Object Detectors RCNN part4

010 Object Detection Postprocessing NonMaximum Suppression

012 Object Detection Performance Metrics

013 Notebooks Description.html

013 section4-object-detection-part1-prepare-data.ipynb.zip

013 section4-object-detection-part2-train-fasterrcnn.ipynb.zip

013 section4-object-detection-part3-train-yolo.ipynb.zip

013 section4-object-detection-part4-measure-performance.ipynb.zip

external-links.txt

05 Semantic Segmentation

001 Introduction to Semantic Segmentation

002 Semantic Segmentation Models

004 Semantic Segmentation in PyTorch

005 Loss Functions for Semantic Segmentation

006 Data Augmentation for Semantic Segmentation

007 Performance Metrics for Semantic Segmentation

008 Notebook Descriptions.html

008 published-model-on-hugging-face-pymlstudio-segment-camvid-fpn-resnet34-.zip

008 section5-semantic-segment-part1-prepare-data.ipynb.zip

008 section5-semantic-segment-part2-train-model.ipynb.zip

external-links.txt

06 Instance and Panoptic Segmentation

001 Introduction to Instance Panoptic Segmentation

003 Instance Segmentation Models

004 Instance Segmentation with Mask RCNN in PyTorch

005 Instance Segmentation with YOLO Ultralytics

006 Performance Metrics for Instance Panoptic Segmentation

007 Notebooks Description.html

007 section6-instance-segment-part1-prepare-data.ipynb.zip

007 section6-instance-segment-part2-train-maskrcnn.ipynb.zip

external-links.txt

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تولید کننده: Udemy