Computer Vision - Fall 2021

Explore comprehensive computer vision concepts through this university-level course from the University of Central Florida's Fall 2021 semester. Begin with foundational topics including linear algebra basics and progress through essential computer vision techniques such as image filtering and edge detection. Master neural networks and convolutional neural networks with detailed multi-part lectures covering architecture, training methodologies, and practical implementation. Gain hands-on experience with PyTorch through dedicated tutorial sessions that demonstrate real-world applications. Delve into advanced feature extraction methods and classification algorithms before advancing to complex topics like object detection using modern deep learning approaches. Learn image segmentation techniques including semantic and instance segmentation methods that are crucial for contemporary computer vision applications. Benefit from expert insights through guest lectures and comprehensive coverage of autoencoders for unsupervised learning tasks. Access over 28 hours of structured content that bridges theoretical foundations with practical implementation skills essential for computer vision practitioners and researchers.

Syllabus

CAP5415 Lecture 1 [Administrative] - Fall2021
CAP5415 Lecture 1 [Introduction to Computer Vision - Part I] - Fall2021
CAP5415 Lecture 2 [Introduction to Computer Vision - Part II] - Fall2021
CAP5415 Lecture 2 [Basics of Linear Algebra - Part I] - Fall2021
CAP5415 Lecture 3 [Basics of Linear Algebra - Part II] - Fall2021
CAP5415 Lecture 4 [Image Filtering - Part I] - Fall2021
CAP5415 Lecture 5 [Image Filtering - Part II] - Fall2021
CAP5415 Lecture 6 [Edge Detection - Part I] - Fall2021
CAP5415 Lecture 7 [Edge Detection - Part II] - Fall2021
CAP5415 Lecture 7 [Introduction to Neural Networks - Part I] - Fall2021
CAP5415 Lecture 8 [Introduction to Neural Networks - Part II] - Fall2021
CAP5415 Lecture 8 [Introduction to Convolution Neural Networks - Part I] - Fall2021
CAP5415 Lecture 9 [Introduction to Convolution Neural Networks - Part II] - Fall2021
CAP5415 Lecture 10 [Introduction to Convolution Neural Networks - Part III] - Fall2021
CAP5415 Lecture 10 [Training Neural Networks - Part I] - Fall2021
CAP5415 Lecture 11 [Training Neural Networks - Part II] - Fall2021
CAP5415 Lecture 12 [PyTorch Tutorial - Part I] - Fall2021
CAP5415 Lecture 13 [PyTorch Tutorial - Part II] - Fall2021
CAP5415 Lecture 14 [Features - Part I] - Fall2021
CAP5415 Lecture 15 [Features - Part II] - Fall2021
CAP5415 Lecture 16 [Features - Part III] - Fall2021
CAP5415 Lecture 17 [Guest Talk - Mubarak Shah] - Fall2021
CAP5415 Lecture 17 [Autoencoder] - Fall2021
CAP5415 Lecture 18 [Classification - Part I] - Fall2021
CAP5415 Lecture 19 [Classification - Part II] - Fall2021
CAP5415 Lecture 20 [Object Detection - Part I] - Fall2021
CAP5415 Lecture 21 [Object Detection - Part II] - Fall2021
CAP5415 Lecture 22 [Object Detection - Part III] - Fall2021
CAP5415 Lecture 23 [Image Segmentation - Part I] - Fall2021
CAP5415 Lecture 24 [Image Segmentation - Part II] - Fall2021
CAP5415 Lecture 25 [Semantic Segmentation] - Fall2021
CAP5415 Lecture 26 [Instance Segmentation] - Fall2021