3068 Repositories
Python deep-search Libraries
Implementation of the master's thesis "Temporal copying and local hallucination for video inpainting".
Temporal copying and local hallucination for video inpainting This repository contains the implementation of my master's thesis "Temporal copying and
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
A deep-learning pipeline for segmentation of ambiguous microscopic images.
Welcome to Official repository of deepflash2 - a deep-learning pipeline for segmentation of ambiguous microscopic images. Quick Start in 30 seconds se
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
Low-dose Digital Mammography with Deep Learning
Impact of loss functions on the performance of a deep neural network designed to restore low-dose digital mammography ====== This repository contains
Stochastic gradient descent with model building
Stochastic Model Building (SMB) This repository includes a new fast and robust stochastic optimization algorithm for training deep learning models. Th
Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization
Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization This repository contains the source code for the paper (link wi
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
MRI reconstruction (e.g., QSM) using deep learning methods
deepMRI: Deep learning methods for MRI Authors: Yang Gao, Hongfu Sun This repo is devloped based on Pytorch (1.8 or later) and matlab (R2019a or later
Code-free deep segmentation for computational pathology
NoCodeSeg: Deep segmentation made easy! This is the official repository for the manuscript "Code-free development and deployment of deep segmentation
KAPAO is an efficient multi-person human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.
KAPAO (Keypoints and Poses as Objects) KAPAO is an efficient single-stage multi-person human pose estimation model that models keypoints and poses as
Point detection through multi-instance deep heatmap regression for sutures in endoscopy
Suture detection PyTorch This repo contains the reference implementation of suture detection model in PyTorch for the paper Point detection through mu
Predict halo masses from simulations via graph neural networks
HaloGraphNet Predict halo masses from simulations via Graph Neural Networks. Given a dark matter halo and its galaxies, creates a graph with informati
Source code for paper "Deep Diffusion Models for Robust Channel Estimation", TBA.
diffusion-channels Source code for paper "Deep Diffusion Models for Robust Channel Estimation". Generic flow: Use 'matlab/main.mat' to generate traini
Extracting knowledge graphs from language models as a diagnostic benchmark of model performance.
Interpreting Language Models Through Knowledge Graph Extraction Idea: How do we interpret what a language model learns at various stages of training?
Collect links to profiles by username through search engines
Marple Summary Collect links to profiles by username through search engines (currently Google and DuckDuckGo). Quick Start ./marple.py soxoj Results:
Python script to check if there is any differences in responses of an application when the request comes from a search engine's crawler.
crawlersuseragents This Python script can be used to check if there is any differences in responses of an application when the request comes from a se
A "finish the lyrics" game using Spotify, YouTube Transcript, and YouTube Search APIs, coupled with visual machine learning
Singify Introducing Singify, the party game! Challenge your friend to who knows songs better. Play random songs from your very own Spotify playlist an
Optimal space decomposition based-product quantization for approximate nearest neighbor search
Optimal space decomposition based-product quantization for approximate nearest neighbor search Abstract Product quantization(PQ) is an effective neare
MASS (Mueen's Algorithm for Similarity Search) - a python 2 and 3 compatible library used for searching time series sub-sequences under z-normalized Euclidean distance for similarity.
Introduction MASS allows you to search a time series for a subquery resulting in an array of distances. These array of distances enable you to identif
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
PySurvival is an open source python package for Survival Analysis modeling
PySurvival What is Pysurvival ? PySurvival is an open source python package for Survival Analysis modeling - the modeling concept used to analyze or p
Deep Survival Machines - Fully Parametric Survival Regression
Package: dsm Python package dsm provides an API to train the Deep Survival Machines and associated models for problems in survival analysis. The under
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo
AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention
AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture
Neural Architecture Search Powered by Swarm Intelligence 🐜
Neural Architecture Search Powered by Swarm Intelligence 🐜 DeepSwarm DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
Alpha Zero General (any game, any framework!) A simplified, highly flexible, commented and (hopefully) easy to understand implementation of self-play
cve-search - a tool to perform local searches for known vulnerabilities
cve-search cve-search is a tool to import CVE (Common Vulnerabilities and Exposures) and CPE (Common Platform Enumeration) into a MongoDB to facilitat
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
ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments.
ModelChimp What is ModelChimp? ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments. ModelChimp provides the followi
🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code
Knock Knock A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of co
Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects
Metaflow Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects. Metaflow
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Gated-Shape CNN for Semantic Segmentation (ICCV 2019)
GSCNN This is the official code for: Gated-SCNN: Gated Shape CNNs for Semantic Segmentation Towaki Takikawa, David Acuna, Varun Jampani, Sanja Fidler
A CV toolkit for my papers.
PyTorch-Encoding created by Hang Zhang Documentation Please visit the Docs for detail instructions of installation and usage. Please visit the link to
reimpliment of DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation
DFANet This repo is an unofficial pytorch implementation of DFANet:Deep Feature Aggregation for Real-Time Semantic Segmentation log 2019.4.16 After 48
Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"
Medical Image Segmentation with Guided Attention This repository contains the code of our paper: "'Multi-scale self-guided attention for medical image
UPSNet: A Unified Panoptic Segmentation Network
UPSNet: A Unified Panoptic Segmentation Network Introduction UPSNet is initially described in a CVPR 2019 oral paper. Disclaimer This repository is te
Understanding Convolution for Semantic Segmentation
TuSimple-DUC by Panqu Wang, Pengfei Chen, Ye Yuan, Ding Liu, Zehua Huang, Xiaodi Hou, and Garrison Cottrell. Introduction This repository is for Under
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)
Learning to Adapt Structured Output Space for Semantic Segmentation Pytorch implementation of our method for adapting semantic segmentation from the s
Tensorflow Implementation of Pixel Transposed Convolutional Networks (PixelTCN and PixelTCL)
Pixel Transposed Convolutional Networks Created by Hongyang Gao, Hao Yuan, Zhengyang Wang and Shuiwang Ji at Texas A&M University. Introduction Pixel
Real-time Joint Semantic Reasoning for Autonomous Driving
MultiNet MultiNet is able to jointly perform road segmentation, car detection and street classification. The model achieves real-time speed and state-
PSPNet in Chainer
PSPNet This is an unofficial implementation of Pyramid Scene Parsing Network (PSPNet) in Chainer. Training Requirement Python 3.4.4+ Chainer 3.0.0b1+
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Multipath RefineNet A MATLAB based framework for semantic image segmentation and general dense prediction tasks on images. This is the source code for
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images
Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K
The repository contains source code and models to use PixelNet architecture used for various pixel-level tasks. More details can be accessed at http://www.cs.cmu.edu/~aayushb/pixelNet/.
PixelNet: Representation of the pixels, by the pixels, and for the pixels. We explore design principles for general pixel-level prediction problems, f
TensorFlow implementation of ENet
TensorFlow-ENet TensorFlow implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. This model was tested on th
TensorFlow implementation of ENet, trained on the Cityscapes dataset.
segmentation TensorFlow implementation of ENet (https://arxiv.org/pdf/1606.02147.pdf) based on the official Torch implementation (https://github.com/e
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation.
ENet This work has been published in arXiv: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. Packages: train contains too
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
ENet in Caffe Execution times and hardware requirements Network 1024x512 1280x720 Parameters Model size (fp32) ENet 20.4 ms 32.9 ms 0.36 M 1.5 MB SegN
Fully convolutional networks for semantic segmentation
FCN-semantic-segmentation Simple end-to-end semantic segmentation using fully convolutional networks [1]. Takes a pretrained 34-layer ResNet [2], remo
Pytorch for Segmentation
Pytorch for Semantic Segmentation This repo has been deprecated currently and I will not maintain it. Meanwhile, I strongly recommend you can refer to
Chainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
fcn - Fully Convolutional Networks Chainer implementation of Fully Convolutional Networks. Installation pip install fcn Inference Inference is done as
FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation
FCN_via_Keras FCN FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This
TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision
TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision @misc{you2019torchcv, author = {Ansheng You and Xiangtai Li and Zhen Zhu a
DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe.
DeepLab Introduction DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe. It combines densely-compute
SegNet-like Autoencoders in TensorFlow
SegNet SegNet is a TensorFlow implementation of the segmentation network proposed by Kendall et al., with cool features like strided deconvolution, a
A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Segnet is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This is implementation of http://arxiv.org/pdf/15
Implementation of SegNet: A Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-Wise Labelling
Caffe SegNet This is a modified version of Caffe which supports the SegNet architecture As described in SegNet: A Deep Convolutional Encoder-Decoder A
Semantic segmentation models, datasets and losses implemented in PyTorch.
Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm
Real-Time Semantic Segmentation in Mobile device
Real-Time Semantic Segmentation in Mobile device This project is an example project of semantic segmentation for mobile real-time app. The architectur
Generic U-Net Tensorflow implementation for image segmentation
Tensorflow Unet Warning This project is discontinued in favour of a Tensorflow 2 compatible reimplementation of this project found under https://githu
U-Net: Convolutional Networks for Biomedical Image Segmentation
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne
A combination of autoregressors and autoencoders using XLNet for sentiment analysis
A combination of autoregressors and autoencoders using XLNet for sentiment analysis Abstract In this paper sentiment analysis has been performed in or
Example Of Splunk Search Query With Python And Splunk Python SDK
SSQAuto (Splunk Search Query Automation) Example Of Splunk Search Query With Python And Splunk Python SDK installation: ➜ ~ git clone https://github.c
Models Supported: AlbUNet [18, 34, 50, 101, 152] (1D and 2D versions for Single and Multiclass Segmentation, Feature Extraction with supports for Deep Supervision and Guided Attention)
AlbUNet-1D-2D-Tensorflow-Keras This repository contains 1D and 2D Signal Segmentation Model Builder for AlbUNet and several of its variants developed
Stack overflow search API
Stack overflow search API
Transformers and related deep network architectures are summarized and implemented here.
Transformers: from NLP to CV This is a practical introduction to Transformers from Natural Language Processing (NLP) to Computer Vision (CV) Introduct
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.
A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.
A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.
Interactive convnet features visualization for Keras
Quiver Interactive convnet features visualization for Keras The quiver workflow Video Demo Build your model in keras model = Model(...) Launch the vis
Keyword-BERT: Keyword-Attentive Deep Semantic Matching
project discription An implementation of the Keyword-BERT model mentioned in my paper Keyword-Attentive Deep Semantic Matching (Plz cite this github r
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica
How to use Microsoft Bing to search for leaks?
Installation In order to install the project, you need install its dependencies: $ pip3 install -r requirements.txt Add your Bing API key to bingKey.t
Predict the latency time of the deep learning models
Deep Neural Network Prediction Step 1. Genernate random parameters and Run them sequentially : $ python3 collect_data.py -gp -ep -pp -pl pooling -num
Yolov5 + Deep Sort with PyTorch
딥소트 수정중 Yolov5 + Deep Sort with PyTorch Introduction This repository contains a two-stage-tracker. The detections generated by YOLOv5, a family of obj
Tensorflow Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE
SMU A Tensorflow Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE arXiv https://arxiv.org/abs/211
Implementation of the bachelor's thesis "Real-time stock predictions with deep learning and news scraping".
Real-time stock predictions with deep learning and news scraping This repository contains a partial implementation of my bachelor's thesis "Real-time
An offline deep reinforcement learning library
d3rlpy: An offline deep reinforcement learning library d3rlpy is an offline deep reinforcement learning library for practitioners and researchers. imp
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
The official implementation of Theme Transformer
Theme Transformer This is the official implementation of Theme Transformer. Checkout our demo and paper : Demo | arXiv Environment: using python versi
Laser device for neutralizing - mosquitoes, weeds and pests
Laser device for neutralizing - mosquitoes, weeds and pests (in progress) Here I will post information for creating a laser device. A warning!! How It
Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.
Homepage | Paper | Datasets | Leaderboard | Documentation Graph Robustness Benchmark (GRB) provides scalable, unified, modular, and reproducible evalu
[NeurIPS'20] Multiscale Deep Equilibrium Models
Multiscale Deep Equilibrium Models 💥 💥 💥 💥 This repo is deprecated and we will soon stop actively maintaining it, as a more up-to-date (and simple
My implementation of Image Inpainting - A deep learning Inpainting model
Image Inpainting What is Image Inpainting Image inpainting is a restorative process that allows for the fixing or removal of unwanted parts within ima
Readings for "A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Therapy, and Drug-Drug Interaction Prediction."
Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp
A python youtube search module
A python youtube search module
For AILAB: Cross Lingual Retrieval on Yelp Search Engine
Cross-lingual Information Retrieval Model for Document Search Train Phase CUDA_VISIBLE_DEVICES="0,1,2,3" \ python -m torch.distributed.launch --nproc_
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
Implementation of Hourglass Transformer, in Pytorch, from Google and OpenAI
Hourglass Transformer - Pytorch (wip) Implementation of Hourglass Transformer, in Pytorch. It will also contain some of my own ideas about how to make
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'21] Pri3D: Can 3D Priors Help 2D Representation Learning?
Pri3D: Can 3D Priors Help 2D Representation Learning? [ICCV 2021] Pri3D leverages 3D priors for downstream 2D image understanding tasks: during pre-tr
RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth, in ICCV 2021 (oral)
RINDNet RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth Mengyang Pu, Yaping Huang, Qingji Guan and Haibin Lin
[ICCV2021] Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving
Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving
The official PyTorch code implementation of "Human Trajectory Prediction via Counterfactual Analysis" in ICCV 2021.
Human Trajectory Prediction via Counterfactual Analysis (CausalHTP) The official PyTorch code implementation of "Human Trajectory Prediction via Count
The official codes for the ICCV2021 presentation "Uniformity in Heterogeneity: Diving Deep into Count Interval Partition for Crowd Counting"
UEPNet (ICCV2021 Poster Presentation) This repository contains codes for the official implementation in PyTorch of UEPNet as described in Uniformity i
Code repo for "Towards Interpretable Deep Networks for Monocular Depth Estimation" paper.
InterpretableMDE A PyTorch implementation for "Towards Interpretable Deep Networks for Monocular Depth Estimation" paper. arXiv link: https://arxiv.or
Code and models for "Rethinking Deep Image Prior for Denoising" (ICCV 2021)
DIP-denosing This is a code repo for Rethinking Deep Image Prior for Denoising (ICCV 2021). Addressing the relationship between Deep image prior and e