930 Repositories
Python weak-shot-classification Libraries
labelpix is a graphical image labeling interface for drawing bounding boxes
Welcome to labelpix 👋 labelpix is a graphical image labeling interface for drawing bounding boxes. 🏠 Homepage Install pip install -r requirements.tx
Implementation of the Paper: "Parameterized Hypercomplex Graph Neural Networks for Graph Classification" by Tuan Le, Marco Bertolini, Frank Noé and Djork-Arné Clevert
Parameterized Hypercomplex Graph Neural Networks (PHC-GNNs) PHC-GNNs (Le et al., 2021): https://arxiv.org/abs/2103.16584 PHM Linear Layer Illustration
(NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductive few-shot classification"
SSR (NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductivefew-shot classification" [Paper] [Project webpage]
Source code for CVPR 2020 paper "Learning to Forget for Meta-Learning"
L2F - Learning to Forget for Meta-Learning Sungyong Baik, Seokil Hong, Kyoung Mu Lee Source code for CVPR 2020 paper "Learning to Forget for Meta-Lear
Spectralformer: Rethinking hyperspectral image classification with transformers
Spectralformer: Rethinking hyperspectral image classification with transformers Danfeng Hong, Zhu Han, Jing Yao, Lianru Gao, Bing Zhang, Antonio Plaza
AWS documentation corpus for zero-shot open-book question answering.
aws-documentation We present the AWS documentation corpus, an open-book QA dataset, which contains 25,175 documents along with 100 matched questions a
Semi-Supervised Learning for Fine-Grained Classification
Semi-Supervised Learning for Fine-Grained Classification This repo contains the code of: A Realistic Evaluation of Semi-Supervised Learning for Fine-G
OpenMMLab Image Classification Toolbox and Benchmark
Introduction English | 简体中文 MMClassification is an open source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project. D
A naive Bayes model for cancer classification using a set of documents
Naivebayes text classifcation model for cancer and noncancer documents Author: Alex King Purpose Requirements/files included How to use 1. Purpose The
Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)
MeTAL - Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning (ICCV2021 Oral) Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaes
R interface to fast.ai
R interface to fastai The fastai package provides R wrappers to fastai. The fastai library simplifies training fast and accurate neural nets using mod
Creating multimodal multitask models
Fusion Brain Challenge The English version of the document can be found here. Обновления 01.11 Мы выкладываем пример данных, аналогичных private test
PoolFormer: MetaFormer is Actually What You Need for Vision
PoolFormer: MetaFormer is Actually What You Need for Vision (arXiv) This is a PyTorch implementation of PoolFormer proposed by our paper "MetaFormer i
cleanlab is the data-centric ML ops package for machine learning with noisy labels.
cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear
Tensorflow 2.x implementation of Vision-Transformer model
Vision Transformer Unofficial Tensorflow 2.x implementation of the Transformer based Image Classification model proposed by the paper AN IMAGE IS WORT
VR-Caps: A Virtual Environment for Active Capsule Endoscopy
VR-Caps: A Virtual Environment for Capsule Endoscopy Overview We introduce a virtual active capsule endoscopy environment developed in Unity that prov
State of the art faster Natural Language Processing in Tensorflow 2.0 .
tf-transformers: faster and easier state-of-the-art NLP in TensorFlow 2.0 ****************************************************************************
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows.
An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu
mmfewshot is an open source few shot learning toolbox based on PyTorch
OpenMMLab FewShot Learning Toolbox and Benchmark
Emotion classification of online comments based on RNN
emotion_classification Emotion classification of online comments based on RNN, the accuracy of the model in the test set reaches 99% data: Large Movie
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in
The pure and clear PyTorch Distributed Training Framework.
The pure and clear PyTorch Distributed Training Framework. Introduction Requirements and Usage Dependency Dataset Basic Usage Slurm Cluster Usage Base
DA2Lite is an automated model compression toolkit for PyTorch.
DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. ⭐ Star us on GitHub — it helps!! Frameworks & Librari
Supervised Classification from Text (P)
MSc-Thesis Module: Masters Research Thesis Language: Python Grade: 75 Title: An investigation of supervised classification of therapeutic process from
Image classification for projects and researches
This is a tool to help you quickly solve classification problems including: data analysis, training, report results and model explanation.
A large-image collection explorer and fast classification tool
IMAX: Interactive Multi-image Analysis eXplorer This is an interactive tool for visualize and classify multiple images at a time. It written in Python
Source code and notebooks to reproduce experiments and benchmarks on Bias Faces in the Wild (BFW).
Face Recognition: Too Bias, or Not Too Bias? Robinson, Joseph P., Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner. "Face recognition:
using STGCN to achieve egg classification task
EEG Classification The task requires us to classify electroencephalography(EEG) into six categories, including human body, human face, animal body,
Python package for covariance matrices manipulation and Biosignal classification with application in Brain Computer interface
pyRiemann pyRiemann is a python package for covariance matrices manipulation and classification through Riemannian geometry. The primary target is cla
Binary LSTM model for text classification
Text Classification The purpose of this repository is to create a neural network model of NLP with deep learning for binary classification of texts re
An interactive dashboard for visualisation, integration and classification of data using Active Learning.
AstronomicAL An interactive dashboard for visualisation, integration and classification of data using Active Learning. AstronomicAL is a human-in-the-
This repository will help you get label for images in Stanford Cars Dataset.
STANFORD CARS DATASET stanford-cars "The Cars dataset contains 16,185 images of 196 classes of cars. The data is split into 8,144 training images and
This project uses unsupervised machine learning to identify correlations between daily inoculation rates in the USA and twitter sentiment in regards to COVID-19.
Twitter COVID-19 Sentiment Analysis Members: Christopher Bach | Khalid Hamid Fallous | Jay Hirpara | Jing Tang | Graham Thomas | David Wetherhold Pro
Dense Gaussian Processes for Few-Shot Segmentation
DGPNet - Dense Gaussian Processes for Few-Shot Segmentation Welcome to the public repository for DGPNet. The paper is available at arxiv: https://arxi
[ArXiv 2021] One-Shot Generative Domain Adaptation
GenDA - One-Shot Generative Domain Adaptation One-Shot Generative Domain Adaptation Ceyuan Yang*, Yujun Shen*, Zhiyi Zhang, Yinghao Xu, Jiapeng Zhu, Z
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization paper Requirements Python = 3.7.10 Pytorch == 1.7
PyTorch implementation of Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network
hierarchical-multi-label-text-classification-pytorch Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach This
Code for IntraQ, PyTorch implementation of our paper under review
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization paper Requirements Python = 3.7.10 Pytorch == 1.7
Flower classification model that classifies flowers in 10 classes made using transfer learning (~85% accuracy).
flower-classification-inceptionV3 Flower classification model that classifies flowers in 10 classes. Training and validation are done using a pre-anot
A multi-platform GUI for bit-based analysis, processing, and visualization
A multi-platform GUI for bit-based analysis, processing, and visualization
The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification".
Rule-based Representation Learner This is a PyTorch implementation of Rule-based Representation Learner (RRL) as described in NeurIPS 2021 paper: Scal
Multi-Content GAN for Few-Shot Font Style Transfer at CVPR 2018
MC-GAN in PyTorch This is the implementation of the Multi-Content GAN for Few-Shot Font Style Transfer. The code was written by Samaneh Azadi. If you
[SIGGRAPH Asia 2019] Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning
AGIS-Net Introduction This is the official PyTorch implementation of the Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning. paper | suppl
Powerful and efficient Computer Vision Annotation Tool (CVAT)
Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our
Code of Classification Saliency-Based Rule for Visible and Infrared Image Fusion
CSF Code of Classification Saliency-Based Rule for Visible and Infrared Image Fusion Tips: For testing: CUDA_VISIBLE_DEVICES=0 python main.py For trai
CLUES: Few-Shot Learning Evaluation in Natural Language Understanding
CLUES: Few-Shot Learning Evaluation in Natural Language Understanding This repo contains the data and source code for baseline models in the NeurIPS 2
Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks
SSRL-for-image-classification Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks
Deploy pytorch classification model using Flask and Streamlit
Deploy pytorch classification model using Flask and Streamlit
Using graph_nets for pion classification and energy regression. Contributions from LLNL and LBNL
nbdev template Use this template to more easily create your nbdev project. If you are using an older version of this template, and want to upgrade to
Code for the TASLP paper "PSLA: Improving Audio Tagging With Pretraining, Sampling, Labeling, and Aggregation".
PSLA: Improving Audio Tagging with Pretraining, Sampling, Labeling, and Aggregation Introduction Getting Started FSD50K Recipe AudioSet Recipe Label E
[NeurIPS 2021] Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data
Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository will provide the official PyTorch implementa
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation (CIKM'17)
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation This is the implementation of RATE: Overcoming Noise and Spar
Code for DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents
DeepXML Code for DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents Architectures and algorithms DeepXML supports
Improving Compound Activity Classification via Deep Transfer and Representation Learning
Improving Compound Activity Classification via Deep Transfer and Representation Learning This repository is the official implementation of Improving C
Solving Zero-Shot Learning in Named Entity Recognition with Common Sense Knowledge
Zero-Shot Learning in Named Entity Recognition with Common Sense Knowledge Associated code for the paper Zero-Shot Learning in Named Entity Recognitio
DataCLUE: 国内首个以数据为中心的AI测评(含模型分析报告)
DataCLUE: A Benchmark Suite for Data-centric NLP You can get the english version of README. 以数据为中心的AI测评(DataCLUE) 内容导引 章节 描述 简介 介绍以数据为中心的AI测评(DataCLUE
Supplementary code for the experiments described in the 2021 ISMIR submission: Leveraging Hierarchical Structures for Few Shot Musical Instrument Recognition.
Music Trees Supplementary code for the experiments described in the 2021 ISMIR submission: Leveraging Hierarchical Structures for Few Shot Musical Ins
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,
Task-related Saliency Network For Few-shot learning
Task-related Saliency Network For Few-shot learning This is an official implementation in Tensorflow of TRSN. Abstract An essential cue of human wisdo
Spectralformer: Rethinking hyperspectral image classification with transformers
The code in this toolbox implements the "Spectralformer: Rethinking hyperspectral image classification with transformers". More specifically, it is detailed as follow.
Short and long time series classification using convolutional neural networks
time-series-classification Short and long time series classification via convolutional neural networks In this project, we present a novel framework f
sktime companion package for deep learning based on TensorFlow
NOTE: sktime-dl is currently being updated to work correctly with sktime 0.6, and wwill be fully relaunched over the summer. The plan is Refactor and
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D
onelearn: Online learning in Python
onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o
Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification tasks
Uniformer - Pytorch Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification ta
Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation
Attention Gated Networks (Image Classification & Segmentation) Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framewor
CNN Based Meta-Learning for Noisy Image Classification and Template Matching
CNN Based Meta-Learning for Noisy Image Classification and Template Matching Introduction This master thesis used a few-shot meta learning approach to
FS-Mol: A Few-Shot Learning Dataset of Molecules
FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluation benchmark which aims to drive few-shot learning research in the domain of molecules and graph-structured data.
Python based framework for Automatic AI for Regression and Classification over numerical data.
Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.
This is the official released code for our paper, The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos
The-Emergence-of-Objectness This is the official released code for our paper, The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos
A Simple LSTM-Based Solution for "Heartbeat Signal Classification and Prediction" in Tianchi
LSTM-Time-Series-Prediction A Simple LSTM-Based Solution for "Heartbeat Signal Classification and Prediction" in Tianchi Contest. The Link of the Cont
A PyTorch Image-Classification With AlexNet And ResNet50.
PyTorch 图像分类 依赖库的下载与安装 在终端中执行 pip install -r -requirements.txt 完成项目依赖库的安装 使用方式 数据集的准备 STL10 数据集 下载:STL-10 Dataset 存储位置:将下载后的数据集中 train_X.bin,train_y.b
IMDB film review sentiment classification based on BERT's supervised learning model.
IMDB film review sentiment classification based on BERT's supervised learning model. On the other hand, the model can be extended to other natural language multi-classification tasks.
Music Classification: Beyond Supervised Learning, Towards Real-world Applications
Music Classification: Beyond Supervised Learning, Towards Real-world Applications
Explainable Zero-Shot Topic Extraction
Zero-Shot Topic Extraction with Common-Sense Knowledge Graph This repository contains the code for reproducing the results reported in the paper "Expl
QAT(quantize aware training) for classification with MQBench
MQBench Quantization Aware Training with PyTorch I am using MQBench(Model Quantization Benchmark)(http://mqbench.tech/) to quantize the model for depl
Alphabetical Letter Recognition
BayeesNetworks-Image-Classification Alphabetical Letter Recognition In these demo we are using "Bayees Networks" Our database is composed by Learning
Alphabetical Letter Recognition
DecisionTrees-Image-Classification Alphabetical Letter Recognition In these demo we are using "Decision Trees" Our database is composed by Learning Im
Supervised multi-SNE (S-multi-SNE): Multi-view visualisation and classification
S-multi-SNE Supervised multi-SNE (S-multi-SNE): Multi-view visualisation and classification A repository containing the code to reproduce the findings
Meta-TTS: Meta-Learning for Few-shot SpeakerAdaptive Text-to-Speech
Meta-TTS: Meta-Learning for Few-shot SpeakerAdaptive Text-to-Speech This repository is the official implementation of "Meta-TTS: Meta-Learning for Few
AI-UPV at IberLEF-2021 EXIST task: Sexism Prediction in Spanish and English Tweets Using Monolingual and Multilingual BERT and Ensemble Models
AI-UPV at IberLEF-2021 EXIST task: Sexism Prediction in Spanish and English Tweets Using Monolingual and Multilingual BERT and Ensemble Models Descrip
AI-UPV at IberLEF-2021 DETOXIS task: Toxicity Detection in Immigration-Related Web News Comments Using Transformers and Statistical Models
AI-UPV at IberLEF-2021 DETOXIS task: Toxicity Detection in Immigration-Related Web News Comments Using Transformers and Statistical Models Description
Leaderboard, taxonomy, and curated list of few-shot object detection papers.
Leaderboard, taxonomy, and curated list of few-shot object detection papers.
TensorFlow 2 implementation of the Yahoo Open-NSFW model
TensorFlow 2 implementation of the Yahoo Open-NSFW model
Penguins species predictor app is used to classify penguins species created using python's scikit-learn, fastapi, numpy and joblib packages.
Penguins Classification App Penguins species predictor app is used to classify penguins species using their island, sex, bill length (mm), bill depth
Classification of EEG data using Deep Learning
Graduation-Project Classification of EEG data using Deep Learning Epilepsy is the most common neurological disease in the world. Epilepsy occurs as a
Obsei is a low code AI powered automation tool.
Obsei is a low code AI powered automation tool. It can be used in various business flows like social listening, AI based alerting, brand image analysis, comparative study and more .
A collection of differentiable SVD methods and also the official implementation of the ICCV21 paper "Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?"
Differentiable SVD Introduction This repository contains: The official Pytorch implementation of ICCV21 paper Why Approximate Matrix Square Root Outpe
[ICCV 2021 Oral] Mining Latent Classes for Few-shot Segmentation
Mining Latent Classes for Few-shot Segmentation Lihe Yang, Wei Zhuo, Lei Qi, Yinghuan Shi, Yang Gao. This codebase contains baseline of our paper Mini
Code for Recurrent Mask Refinement for Few-Shot Medical Image Segmentation (ICCV 2021).
Recurrent Mask Refinement for Few-Shot Medical Image Segmentation Steps Install any missing packages using pip or conda Preprocess each dataset using
PyTorch implementation of our ICCV paper DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection.
Introduction This repo contains the official PyTorch implementation of our ICCV paper DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection. Up
Parametric Contrastive Learning (ICCV2021)
Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or
Official implementation of Few-Shot and Continual Learning with Attentive Independent Mechanisms
Few-Shot and Continual Learning with Attentive Independent Mechanisms This repository is the official implementation of Few-Shot and Continual Learnin
[ICCV2021] Official Pytorch implementation for SDGZSL (Semantics Disentangling for Generalized Zero-Shot Learning)
Semantics Disentangling for Generalized Zero-shot Learning This is the official implementation for paper Zhi Chen, Yadan Luo, Ruihong Qiu, Zi Huang, J
Codes for the ICCV'21 paper "FREE: Feature Refinement for Generalized Zero-Shot Learning"
FREE This repository contains the reference code for the paper "FREE: Feature Refinement for Generalized Zero-Shot Learning". [arXiv][Paper] 1. Prepar
Official code and pretrained models for CTRL-C (Camera calibration TRansformer with Line-Classification).
CTRL-C: Camera calibration TRansformer with Line-Classification This repository contains the official code and pretrained models for CTRL-C (Camera ca
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition How Fast Compare to Other Zero-Shot NAS Proxies on CIFAR-10/100 Pre-trained Model
Efficient Training of Audio Transformers with Patchout
PaSST: Efficient Training of Audio Transformers with Patchout This is the implementation for Efficient Training of Audio Transformers with Patchout Pa
Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification
Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification