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Official Pytorch implementation of CutMix regularizer

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021)

An open-source toolkit which is full of handy functions, including the most used models and utilities for deep-learning practitioners!

Official PyTorch implementation of DiffuseMix : Label-Preserving Data Augmentation with Diffusion Models (CVPR'2024)

Implementation of modern data augmentation techniques in TensorFlow 2.x to be used in your training pipeline.

Keras implementation of CutMix regularizer

Official Codes and Pretrained Models for RecursiveMix

FastClassification is a tensorflow toolbox for class classification. It provides a training module with various backbones and training tricks towards state-of-the-art class classification.

tensorflow2 implementation of SnapMix as described in SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data

Implementation of an advanced Convolutional Neural Network (CNN) for large-scale pest recognition, incorporating augmentation techniques and regularizers for improved accuracy and generalization.

This is a TensorFlow implementation of the following paper: DropBlock: A regularization method for convolutional networks

PyTorch implementation of 'ViT' (Dosovitskiy et al., 2020) and training it on CIFAR-10 and CIFAR-100

Tensorflow2(Keras)のImageDataGeneratorのJupyter上での実行例。

Implementation of CutMix Augmentation with Keras.

Tensorflow2/KerasのImageDataGenerator向けのcutmixの実装。

Deep learning solution for Cassava Leaf Disease Classification, a Kaggle's Research Code Competition using Tensorflow.

DualDet implementation using PyTorch

Image Classification Using Swin Transformer With RandAugment, CutMix, and MixUp