Deep Learning for Image Segmentation with Python & Pytorch
Image Semantic Segmentation for Computer Vision with PyTorch & Python to Train & Deploy YOUR own Models (UNet, DeepLab)
4.50 (208 reviews)
872
students
3.5 hours
content
Feb 2025
last update
$49.99
regular price
What you will learn
Learn Image Semantic Segmentation Complete Pipeline and its Real-world Applications with Python & PyTorch
Deep Learning Architectures for Semantic Segmentation (UNet, DeepLabV3, PSPNet, PAN, UNet++, MTCNet etc.)
Segmentation with Pretrained Pytorch Models (FCN, DeepLabV3) on COCO Dataset
Perform Image Segmentation with Deep Learning Models on Custom Datasets
Datasets and Data Annotations Tool for Semantic Segmentation
Data Augmentation and Data Loaders Implementation in PyTorch
Learn Performance Metrics (IOU, etc.) for Segmentation Models Evaluation
Transfer Learning and Pretrained Deep Resnet Architecture
Implement Segmentation Models (UNet, PSPNet, DeepLab, PAN, UNet++) in PyTorch using different Encoder and Decoder Architectures
Learn to Optimize Hyperparameters for Segmentation Models to Improve the Performance during Training on Custom Dataset
Test Segmentation Trained Model and Calculate IOU, Class-wise IOU, Pixel Accuracy, Precision, Recall and F-score
Visualize Segmentation Results and Generate RGB Predicted Output Segmentation Map
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5092818
udemy ID
17/01/2023
course created date
28/01/2023
course indexed date
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