PyTorch implementation of Fast AutoAugment for Time Series
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Updated
May 16, 2024 - Python
PyTorch implementation of Fast AutoAugment for Time Series
A treasure chest for visual classification and recognition powered by PaddlePaddle
🛠 Toolbox to extend PyTorch functionalities
List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.
Predefined pipelines for image augmentation
Unofficial PyTorch Reimplementation of RandAugment.
Official PyTorch code for CVPR 2021 paper "AutoDO: Robust AutoAugment for Biased Data with Label Noise via Scalable Probabilistic Implicit Differentiation"
This repository contains the code and the report for the coursework of INFR11031 Advanced Vision, a postgraduate course offered at The University of Edinburgh. The task was to train on limited and improve the accuracy of the ResNet-50 classifier on a small subset of the ImageNet dataset containing 50K training images and 50K test images. Achieve…
Collection of deep learning modules
Comparing different learning paradigms on the STL 10 dataset and carrying further analysis in each method
Unofficial Pytorch implementation of the paper 'Learning Data Augmentation Strategies for Object Detection'
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.
Unofficial Pytorch Implementation Of AdversarialAutoAugment(ICLR2020)
📦Simple Tool Box with Pytorch
Optimize RandAugment with differentiable operations
Stanford CS 230 Group Project
Unofficial PyTorch Reimplementation of UniformAugment.
Code for "OnlineAugment: Online Data Augmentation with Less Domain Knowledge" (ECCV 2020)
PyTorch implementation of AutoAugment.
RandAugment process for point cloud data to handle with 3D classification task
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