Open source code for paper "Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere" ICML 2020

A curated list of foundation models for vision and language tasks

The state-of-the-art image restoration model without nonlinear activation functions.

AI based multi-label girl image classification system, implemented by using TensorFlow.

experiments on Paper <Bag of Tricks for Image Classification with Convolutional Neural Networks> and other useful tricks to improve CNN acc

Image classification for everyone.

An end-to-end PyTorch framework for image and video classification

Image classification: efficientnet/resnest/seresnext/.....

A tool using OpenCV to annotate images for image classification, optical character reading, ...

Classification of the Hyperspectral Image Indian Pines with Convolutional Neural Network

Categorizing food and grocery products using Transfer Learning from Inception V3

Simple Image Classification Models for the CIFAR-10 dataset using TensorFlow

Keras- Multi Label Image Classification

Codebase for Image Classification Research, written in PyTorch.

CNN for multi-class image recognition in tensorflow

deep learning for image processing including classification and object-detection etc.

A curated list of deep learning image classification papers and codes

Imitation learning algorithms with Co-training for Mobile ALOHA: ACT, Diffusion Policy, VINN

this is for myself, development roadmap

Code for "Stochastic Optimization of Sorting Networks using Continuous Relaxations", ICLR 2019.

A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.

PyTorch Implementation of Deep Hierarchical Classification for Category Prediction in E-commerce System

JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf

Fast Food Memes monolith https://t.me/ffmemesbot

Code for the paper "A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks".

An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.

🏭 Collaboratively build, visualize, and design neural nets in browser

A dataset of datasets for learning to learn from few examples

Deep Learning with Catalyst