Month 7: Computer Vision
Week 1: Image Processing and Feature Extraction
- Day 1: Introduction to Computer Vision and Image Processing
- Day 2: Image Filters, Gradients, and Edges
- Day 3: Feature Extraction: HOG, SIFT, SURF
- Day 4: Color Spaces and Histograms
- Day 5: Practical application and a mini-project
Week 2: Object Detection and Recognition
- Day 1: Introduction to Object Detection
- Day 2: Haar Cascades, Histogram of Oriented Gradients (HOG)
- Day 3: Introduction to Convolutional Neural Networks (CNNs) for Object Recognition
- Day 4: R-CNN, Fast R-CNN, and Faster R-CNN
- Day 5: Single Shot MultiBox Detector (SSD), You Only Look Once (YOLO)
Week 3: Image Segmentation and Localization
- Day 1: Introduction to Image Segmentation
- Day 2: Segmentation Algorithms: Thresholding, Edge-based segmentation
- Day 3: Semantic Segmentation: Fully Convolutional Networks (FCNs)
- Day 4: Instance Segmentation: Mask R-CNN
- Day 5: Practical application and a mini-project
Week 4: Style Transfer and Image Synthesis
- Day 1: Introduction to Style Transfer: Neural Style Transfer
- Day 2: Advanced Style Transfer: CycleGAN
- Day 3: Introduction to Image Synthesis: GANs
- Day 4: Advanced Image Synthesis: DCGAN, StyleGAN
- Day 5: Practical application and a mini-project
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