Computer Vision Fundamentals

17 lessons in AI Fundamentals

• Real-World Computer Vision ApplicationsSlides / Video
• Common CV ChallengesSlides / Video
• Evaluation Metrics: IoU and mAPSlides / Video
• Transfer Learning with Pretrained Vision ModelsSlides / Video
• Image Segmentation: Semantic vs InstanceSlides / Video
• Object Detection and Bounding BoxesSlides / Video
• Image Classification TaskSlides / Video
• Edge Detection and Classical FeaturesSlides / Video
• CNN Architecture for Vision TasksSlides / Video
• Pooling Layers and DownsamplingSlides / Video
• Feature Maps and Learned Visual FeaturesSlides / Video
• Convolution and Kernels ExplainedSlides / Video
• Image Augmentation TechniquesSlides / Video
• Image Preprocessing EssentialsSlides / Video
• Color Spaces: RGB, Grayscale, HSVSlides / Video
• How Digital Images Are RepresentedSlides / Video
• What Computer Vision IsSlides / Video