1211 Open source projects that are alternatives of or similar to well-classified-examples-are-underestimated

Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification. ICIAR 2018 Grand Challenge on BreAst Cancer Histology images (BACH)

Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification

RMDL: Random Multimodel Deep Learning for Classification

Ramp up your custom natural language processing (NLP) task, allowing you to bring your own data, use your preferred frameworks and bring models into production.

KitanaQA: Adversarial training and data augmentation for neural question-answering models

Deep learning, Convolutional neural networks, Image processing, Document processing, Table detection, Page object detection, Table classification. https://www.sciencedirect.com/science/article/pii/S0925231221018142

A collection of SOTA Image Classification Models in PyTorch

Implementation of State-of-the-art Text Classification Models in Pytorch

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

An Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches

Catalyst.Classification

Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.

Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas

Official code for Conformer: Local Features Coupling Global Representations for Visual Recognition

Parametric Contrastive Learning (ICCV2021)

Pytorch implementation of network design paradigm described in the paper "Designing Network Design Spaces"

Keras implementation of a ResNet-CAM model

Robust Out-of-distribution Detection in Neural Networks

From Random Walks to Transformer for Learning Node Embeddings (ECML-PKDD 2020) (In Pytorch and Tensorflow)

Transfer Learning Suite in Keras. Perform transfer learning using any built-in Keras image classification model easily!

Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"

NLP research：基于tensorflow的nlp深度学习项目，支持文本分类/句子匹配/序列标注/文本生成 四大任务

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Use machine learning in AppInventor, with easy training using text, images, or numbers through the Machine Learning for Kids website.

Implementation of EfficientNet model. Keras and TensorFlow Keras.

Unofficial implementation of Google's FNet: Mixing Tokens with Fourier Transforms

Sandbox for training deep learning networks

Code for the CHAMPS Predicting Molecular Properties Kaggle competition

Object classification with CIFAR-10 using transfer learning

TrojanZoo provides a universal pytorch platform to conduct security researches (especially backdoor attacks/defenses) of image classification in deep learning.

Representing Long-Range Context for Graph Neural Networks with Global Attention

This is an official implementation of our NeurIPS 2021 paper "HRFormer: High-Resolution Transformer for Dense Prediction".

HTTP service for Tensorflow images classification model

GUI-based software for training, evaluating and applying deep neural nets for image classification

Final Project of the Udacity AI Programming with Python Nanodegree

Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper

[ICCV2021] Official PyTorch implementation of Segmenter: Transformer for Semantic Segmentation

The official SNOMED CT OWL Toolkit. OWL conversion, classification and authoring support.

Image classification of wildflowers using deep residual learning and convolutional neural nets

Multi-class classification with focal loss for imbalanced datasets

End-to-end Temporal Action Detection with Transformer. [Under review for a journal publication]

A Multi-Class Brain Tumor Classifier using Convolutional Neural Network with 99% Accuracy achieved by applying the method of Transfer Learning using Python and Pytorch Deep Learning Framework

D-Lab's 6 hour introduction to machine learning in Python. Learn how to perform classification, regression, clustering, and do model selection using scikit-learn and TPOT.

Unofficial implementation of MaX-DeepLab for Instance Segmentation

GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)

Transfromer tensorflow2.0版本实现

Embedding模型代码和学习笔记总结

Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"

This repo contains projects created using TensorFlow-Lite on Raspberry Pi and Teachable Machine. AI and ML capabilities have been integrated with Robot's software.

Food classification using deep learning

A set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch based deep neural networks.

PyTorch v1.2에서 생긴 Transformer API 를 이용한 간단한 Chitchat 챗봇

Probabilistic question-asking system: the program asks, the users answer. The minimal goal of the program is to identify what the user needs (a target), even if the user is not aware of the existence of such a thing/product/service.

This project is to use deep learning to auto classify the scene images with limited amount of training images.

Neutron: A pytorch based implementation of Transformer and its variants.

[CVPR 2022--Oral] Restormer: Efficient Transformer for High-Resolution Image Restoration. SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.

This library provides a set of basic functions for different type of deep learning (and other) algorithms in C.This deep learning library will be constantly updated

To detect any reasonable change in a live cctv to avoid large storage of data. Once, we notice a change, our goal would be track that object or person causing it. We would be using Computer vision concepts. Our major focus will be on Deep Learning and will try to add as many features in the process.

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