Exploring CNNs and model quantization on Caltech-256 dataset
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Updated
Nov 1, 2017 - Jupyter Notebook
Exploring CNNs and model quantization on Caltech-256 dataset
257-way Image Classification using Fully Connected Neural Network, Convolutional Neural Network built from scratch and Transfer Learning
Transfer learning on VGG16 using Keras with Caltech256 and Urban Tribes dataset. Dark knowledge in transfer learning.
Classic nets(AlexNet, VGG, ResNet) implemented by pytorch. Caltech256 for training.
Image recognition on CIFAR 10, CIFAR 100, Caltech 101 and Caltech 256 datasets. With the implementation of WideResNet, InceptionV3 and DenseNet neural networks.
Image Classification Using Swin Transformer With RandAugment, CutMix, and MixUp
Image classification using transfer learning in convolutional neural networks.
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