The topics to be covered include: Introduction to Computer Vision. Architecture & Paradigms for computational vision. Relation to human visual perception. Mathematical techniques for representing and reasoning, with curves, surfaces and volumes. Illumination and reflectance models. Color perception. Image segmentation and aggregation. Pixel Intensity Histograms; their philosophy, features, and process. Convolution function. Types of Computer Vision problems; Classification, Classification with localization, object detection, and instance segmentation. Digital Images, pixels, and amplitude quantization. Python, Keras, OpenCV
- Teacher: Abubakar Jauro Sani