AI Reading List: Technologies: Image Recognition

Below is a portion of my informal list of readings related to Artificial Intelligence (AI). This started out as a very short list created for use in conjunction with an academic presentation and has now grown much larger. Please let me know if you have any corrections, additions, suggestions, etc. It is very idiosyncratic and not meant to be comprehensive. Please feel free to share with others.


Artificial Intelligence (AI) Reading List, by Philip Rubin

Technologies — Image Recognition:

Yann LeCun, et al. Backpropagation Applied to Handwritten Zip Code Recognition. Neural Computation, 1, 541-551, 1989.

Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner. Gradient Based Learning Applied to Document Recognition. Proceedings of IEEE, 86(11), 2278–2324, 1998.

Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. ImageNet: A Large-Scale Hierarchical Image Database. IEEE Conference on Computer Vision and Pattern Recognition, 2009.

Andrej Karpathy. The state of Computer Vision and AI: we are really, really far away. Andrej Karpathy Blog, Oct. 22, 2012.

Douglas Heaven. Why deep-learning AIs are so easy to fool. Nature.com, Oct. 9, 2019.

Nathan Hughes, Yun Chang, and Luca Carlone. Hydra: A Real-time Spatial Perception Engine for 3D Scene Graph Construction and Optimization. arXiv:2201.13360, Jan. 31, 2022. See, also: YouTube video.

Kashmir Hill. Accused of Cheating by an Algorithm, and a Professor She Had Never Met. nytimes.com, May 27, 2022.

Andrej Karpathy. Deep Neural Nets: 33 years ago and 33 years from nowAndrej Karpathy Blog, Mar. 14, 2022. 

Wikipedia. Image recognition.


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