Image Classification Training Framework for Network Distillation
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Updated
Oct 7, 2022 - Python
Image Classification Training Framework for Network Distillation
Merged Geometrical Homogeneous Clustering for Image Data Reduction. An algorithm to reduce large image datasets maintaining similar accuracy.
Official PyTorch Implementation of Guarding Barlow Twins Against Overfitting with Mixed Samples
Implémentation du papier Colorization Transformer (ICLR 2021) - Version Expérimentale
The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".
mini-imagenet and tiny-imagent dataset transformation for traditional classification task and also for the format for few-shot learning / meta-learning tasks
Official PyTorch Implementation for the "Distilling Datasets Into Less Than One Image" paper.
An implementation of MobileNetV3 with pyTorch
Image classification on Tiny ImageNet
🔬 Some personal research code on analyzing CNNs. Started with a thorough exploration of Stanford's Tiny-Imagenet-200 dataset.
PyTorch custom dataset APIs -- CUB-200-2011, Stanford Dogs, Stanford Cars, FGVC Aircraft, NABirds, Tiny ImageNet, iNaturalist2017
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
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