Sandbox for training deep learning networks
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Updated
Sep 6, 2024 - Python
Sandbox for training deep learning networks
Proper implementation of ResNet-s for CIFAR10/100 in pytorch that matches description of the original paper.
The official implementation of [CVPR2022] Decoupled Knowledge Distillation https://arxiv.org/abs/2203.08679 and [ICCV2023] DOT: A Distillation-Oriented Trainer https://openaccess.thecvf.com/content/ICCV2023/papers/Zhao_DOT_A_Distillation-Oriented_Trainer_ICCV_2023_paper.pdf
PyTorch implementation of CNNs for CIFAR benchmark
Unofficial PyTorch Reimplementation of RandAugment.
Implementation of the mixup training method
Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)
TensorFlow implementation of GoogLeNet and Inception for image classification.
Open Set Recognition
Implementation of our Pattern Recognition paper "DMT: Dynamic Mutual Training for Semi-Supervised Learning"
[TIP 2022] Towards Better Accuracy-efficiency Trade-offs: Divide and Co-training. Plus, an image classification toolbox includes ResNet, Wide-ResNet, ResNeXt, ResNeSt, ResNeXSt, SENet, Shake-Shake, DenseNet, PyramidNet, and EfficientNet.
The official implementation of paper: "Inter-Instance Similarity Modeling for Contrastive Learning"
Training ImageNet / CIFAR models with sota strategies and fancy techniques such as ViT, KD, Rep, etc.
Python toolkit for speech processing
✨基于卷积神经网络(CNN)和CIFAR10数据集的图像智能分类 Web 应用 Intelligent Image Classification Web Applcation based on Convolutional Neural Networks and the CIFAR10 Dataset✨🚩 (with README in English) 📌含在线demo:图像分类可视化界面,快速部署深度学习模型为网页应用,Web预测系统,决策支持系统(DSS),图像分类前端网页,图像分类Demo展示-Pywebio。AI人工智能图像分类-Pytorch。CIFAR10数据集,小模型。100%纯Python代码,轻量化,易复现
Python implementation of "Deep Residual Learning for Image Recognition" (http://arxiv.org/abs/1512.03385 - MSRA, winner team of the 2015 ILSVRC and COCO challenges).
The official implementation of "Asymmetric Patch Sampling for Contrastive Learning"
SE-Net Incorporates with ResNet and WideResnet on CIFAR-10/100 Dataset.
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