- 1943: McCulloch & Pitts - A logical calculus of the ideas immanent in nervous activity
- 1950s: Hubel & Wiesel - Cat Experiment & Basis of Visual Perception
- 1958: Rosenblatt - The Perceptron: A Probabalistic Model For Information Storage And Organization In The Brain
- 1980: Fukushima - Neocognitron: A Self-organizing Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position
- 1986: Hinton, Rumelhart, & Williams - Learning Representations by back-propogating errors
- 1989: LeCun & Friends - Backpropogation Applied to Handwritten Zip Code Recognition
- 2001: Viola & Jones - Rapid Object Detection using a Boosted Cascade of Simple Features
- 2006: Hinton, Osindero, & Teh - A fast learning algorithm for deep belief nets
- 2011: Glorot, Bordes, & Bengio - Deep Sparse Rectifier Neural Networks
- 2014: Krizhevsky, Sutskever, Hinton - ImageNet Classification with Deep Convolutional Neural Networks
Intro to Computer Vision & Neural Nets
Intro to Data Science: Python and SQL (1/29/19 - 3/21/19)
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