Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet

PyTorch custom dataset APIs -- CUB-200-2011, Stanford Dogs, Stanford Cars, FGVC Aircraft, NABirds, Tiny ImageNet, iNaturalist2017

🔬 Some personal research code on analyzing CNNs. Started with a thorough exploration of Stanford's Tiny-Imagenet-200 dataset.

Image classification on Tiny ImageNet

An implementation of MobileNetV3 with pyTorch

Official PyTorch Implementation for the "Distilling Datasets Into Less Than One Image" paper.

mini-imagenet and tiny-imagent dataset transformation for traditional classification task and also for the format for few-shot learning / meta-learning tasks

The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".

Image Tagger: AI-based Android App for Automated Image Annotation

Implémentation du papier Colorization Transformer (ICLR 2021) - Version Expérimentale

Official PyTorch Implementation of Guarding Barlow Twins Against Overfitting with Mixed Samples

A Steganography model that uses Deep Learning in order to hide secret images within covers, making it impossible to be deciphered by the naked eye.

Tensorflow implementation of Image Matching with Triplet Loss on the Tiny ImageNet dataset.

Merged Geometrical Homogeneous Clustering for Image Data Reduction. An algorithm to reduce large image datasets maintaining similar accuracy.

Code and final submission for the Tiny ImageNet Challenge. Trained on Google colab and finished top 5 among 1072 participants

Image Classification Training Framework for Network Distillation

Challenge: Apply advanced computer vision concepts (CNN only) and beat state-of-the-art using constrained resources and concepts.