Deep Learning for Computer Vision（Cite）

date
Dec 16, 2022
slug
DLCV
status
Published
tags
Website
summary
type
Post
re
Research
Lecture 2: Image Classification
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John Canny, “A Computational Approach to Edge Detection”, IEEE TPAMI 1986
Edge Detection
Alex Krizhevsky, “Learning Multiple Layers of Features from Tiny Images”, Technical Report, 2009.
CIFAR100
Deng et al, “ImageNet: A Large-Scale Hierarchical Image Database”, CVPR 2009
ImageNet
Russakovsky et al, “ImageNet Large Scale Visual Recognition Challenge”, IJCV 2015
ImageNet
Zhou et al, “Places: A 10 million Image Database for Scene Recognition”, TPAMI 2017
MIT Places
Lake et al, “Human-level concept learning through probabilistic program induction”, Science, 2015
Omniglot
Devlin et al, “Exploring Nearest Neighbor Approaches for Image Captioning”, 2015
Nearest Neighbor
Lecture 3: Linear Classifiers
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Lecture 4: Regularization + Optimization
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Sutskever et al, “On the importance of initialization and momentum in deep learning”, ICML 2013
SGD + Momentum
Duchi et al, “Adaptive subgradient methods for online learning and stochastic optimization”, JMLR 2011
AdaGrad
Kingma and Ba, “Adam: A method for stochastic optimization”, ICLR 2015
Adam
Loshchilov and Hutter, “Decoupled Weight Decay Regularization”, ICLR 2019
AdamW
 
Lecture 5: Neural Networks
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