Artificial Intelligence · Computer Vision
A topic within Computer Vision, itself one of 11 topics in that field and part of Artificial Intelligence.
No prior grounding assumed.
Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition
Stanford University School of Engineering · 2017
Opens Stanford's CS231n course by tracing computer vision from early edge-detection theory to the ImageNet moment, framing the rest of the course as…
Assumes you know the vocabulary.
Computer Vision: Algorithms and Applications
Richard Szeliski · 2010
Walks the working vision pipeline — features, alignment, stereo, motion, recognition — keeping each piece of mathematics next to the application that…
Primary sources and full treatments.
Stanford CS231n: Convolutional Neural Networks for Visual Recognition
Fei-Fei Li, Justin Johnson and Serena Yeung (Stanford) · 2017
Builds computer vision up from linear classifiers to convolutional architectures, arguing that learned features replaced hand-designed ones because…
3 works
Stanford University School of Engineering
Opens Stanford's CS231n course by tracing computer vision from early edge-detection theory to the ImageNet moment, framing the rest of the course as the story of why learned features replaced hand-designed ones.
68 minuteslink checked 17 Sept 2026Richard Szeliski
Walks the working vision pipeline — features, alignment, stereo, motion, recognition — keeping each piece of mathematics next to the application that needs it.
link checked 17 Sept 2026Fei-Fei Li, Justin Johnson and Serena Yeung (Stanford)
Builds computer vision up from linear classifiers to convolutional architectures, arguing that learned features replaced hand-designed ones because the data finally supported it.
link checked 17 Sept 2026