Image classification on Caltech101 using CNNs

Training of Convolutional Neural Networks for image classification on dataset Caltech-101 using AlexNet, VGG-11 and ResNet-18 architectures with transfer learning from ImageNet.

For all the details on the learning process and implementation see the final report

Useful resources in this repo:

• assignment
• code
• report

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References

[1] Krizhevsky, Alex & Sutskever, Ilya & Hinton, Geoffrey. (2012). ImageNet Classification with Deep Convolutional Neural Networks. Neural Information Processing Systems. 25. 10.1145/3065386 - paper

[2] Li Fei-Fei, R. Fergus and P. Perona, "Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories," 2004 Conference on Computer Vision and Pattern Recognition Workshop, Washington, DC, USA, 2004, pp. 178-178, doi: 10.1109/CVPR.2004.383. - paper

[3] Dataset - github