1846 Repositories
Python customer-segmentation-analysis Libraries
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
GCNet for Object Detection By Yue Cao, Jiarui Xu, Stephen Lin, Fangyun Wei, Han Hu. This repo is a official implementation of "GCNet: Non-local Networ
The code for Expectation-Maximization Attention Networks for Semantic Segmentation (ICCV'2019 Oral)
EMANet News The bug in loading the pretrained model is now fixed. I have updated the .pth. To use it, download it again. EMANet-101 gets 80.99 on the
Python data processing, analysis, visualization, and data operations
Python This is a Python data processing, analysis, visualization and data operations of the source code warehouse, book ISBN: 9787115527592 Descriptio
A basic neural network for image segmentation.
Unet_erythema_detection A basic neural network for image segmentation. 前期准备 1.在logs文件夹中下载h5权重文件,百度网盘链接在logs文件夹中 2.将所有原图 放置在“/dataset_1/JPEGImages/”文件夹
Unsupervised text tokenizer focused on computational efficiency
YouTokenToMe YouTokenToMe is an unsupervised text tokenizer focused on computational efficiency. It currently implements fast Byte Pair Encoding (BPE)
Sentiment analysis translations of the Bhagavad Gita
Sentiment and Semantic Analysis of Bhagavad Gita Translations It is well known that translations of songs and poems not only breaks rhythm and rhyming
Code for Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task
BRATS 2021 Solution For Segmentation Task This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmenta
Fully Adaptive Bayesian Algorithm for Data Analysis (FABADA) is a new approach of noise reduction methods. In this repository is shown the package developed for this new method based on \citepaper.
Fully Adaptive Bayesian Algorithm for Data Analysis FABADA FABADA is a novel non-parametric noise reduction technique which arise from the point of vi
Performance Analysis of Multi-user NOMA Wireless-Powered mMTC Networks: A Stochastic Geometry Approach
Performance Analysis of Multi-user NOMA Wireless-Powered mMTC Networks: A Stochastic Geometry Approach Thanh Luan Nguyen, Tri Nhu Do, Georges Kaddoum
A Small and Easy approach to the BraTS2020 dataset (2D Segmentation)
BraTS2020 A Light & Scalable Solution to BraTS2020 | Medical Brain Tumor Segmentation (2D Segmentation) Developed the segmentation models for segregat
Best practices for segmentation of the corporate network of any company
Best-practice-for-network-segmentation What is this? This project was created to publish the best practices for segmentation of the corporate network
This project consists of data analysis and data visualization (done using python)of all IPL seasons from 2008 to 2019 and answering the most asked questions about the IPL.
IPL-data-analysis This project consists of data analysis and data visualization of all IPL seasons from 2008 to 2019 and answering the most asked ques
GLNet for Memory-Efficient Segmentation of Ultra-High Resolution Images
GLNet for Memory-Efficient Segmentation of Ultra-High Resolution Images Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth
Instance segmentation by jointly optimizing spatial embeddings and clustering bandwidth This codebase implements the loss function described in: Insta
LEDNet: A Lightweight Encoder-Decoder Network for Real-time Semantic Segmentation
LEDNet: A Lightweight Encoder-Decoder Network for Real-time Semantic Segmentation Table of Contents: Introduction Project Structure Installation Datas
LightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation
LightNet++ !!!New Repo.!!! ⇒ EfficientNet.PyTorch: Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights !!
Proposal, Tracking and Segmentation (PTS): A Cascaded Network for Video Object Segmentation
Proposal, Tracking and Segmentation (PTS): A Cascaded Network for Video Object Segmentation By Qiang Zhou*, Zilong Huang*, Lichao Huang, Han Shen, Yon
[PAMI 2020] Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation
Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation This repository contains the source code for
MaskTrackRCNN for video instance segmentation based on mmdetection
MaskTrackRCNN for video instance segmentation Introduction This repo serves as the official code release of the MaskTrackRCNN model for video instance
Deep Watershed Transform for Instance Segmentation
Deep Watershed Transform Performs instance level segmentation detailed in the following paper: Min Bai and Raquel Urtasun, Deep Watershed Transformati
FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics
FusionNet_Pytorch FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics Requirements Pytorch 0.1.11 Pyt
Fully Connected DenseNet for Image Segmentation
Fully Connected DenseNets for Semantic Segmentation Fully Connected DenseNet for Image Segmentation implementation of the paper The One Hundred Layers
OBG-FCN - implementation of 'Object Boundary Guided Semantic Segmentation'
OBG-FCN This repository is to reproduce the implementation of 'Object Boundary Guided Semantic Segmentation' in http://arxiv.org/abs/1603.09742 Object
Code release for Hu et al. Segmentation from Natural Language Expressions. in ECCV, 2016
Segmentation from Natural Language Expressions This repository contains the code for the following paper: R. Hu, M. Rohrbach, T. Darrell, Segmentation
Caffe implementation for Hu et al. Segmentation for Natural Language Expressions
Segmentation from Natural Language Expressions This repository contains the Caffe reimplementation of the following paper: R. Hu, M. Rohrbach, T. Darr
TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network
TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network Created by Seunghoon Hong, Junhyuk Oh,
Project for the discipline of Visual Data Analysis at EMAp FGV.
Analysis of the dissemination of fake news about COVID-19 on Twitter This project was the final work for the discipline of Visual Data Analysis of the
The final project of "Applying AI to EHR Data" of "AI for Healthcare" nanodegree - Udacity.
Patient Selection for Diabetes Drug Testing Project Overview EHR data is becoming a key source of real-world evidence (RWE) for the pharmaceutical ind
Use graph-based analysis to re-classify stocks and to improve Markowitz portfolio optimization
Dynamic Stock Industrial Classification Use graph-based analysis to re-classify stocks and experiment different re-classification methodologies to imp
The final project of "Applying AI to 3D Medical Imaging Data" from "AI for Healthcare" nanodegree - Udacity.
Quantifying Hippocampus Volume for Alzheimer's Progression Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder that result
Self-supervised spatio-spectro-temporal represenation learning for EEG analysis
EEG-Oriented Self-Supervised Learning and Cluster-Aware Adaptation This repository provides a tensorflow implementation of a submitted paper: EEG-Orie
Madanalysis5 - A package for event file analysis and recasting of LHC results
Welcome to MadAnalysis 5 Outline What is MadAnalysis 5? Requirements Downloading
Weakly-supervised semantic image segmentation with CNNs using point supervision
Code for our ECCV paper What's the Point: Semantic Segmentation with Point Supervision. Summary This library is a custom build of Caffe for semantic i
Generic Foreground Segmentation in Images
Pixel Objectness The following repository contains pretrained model for pixel objectness. Please visit our project page for the paper and visual resul
Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).
Weakly Supervised Segmentation with TensorFlow This repo contains a TensorFlow implementation of weakly supervised instance segmentation as described
MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research
MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research.The pipeline is based on nn-UNet and has the capability to segment 120 unique tissue classes from a whole-body 18F-FDG PET/CT image.
Semantic Segmentation with SegFormer on Drone Dataset.
SegFormer_Segmentation Semantic Segmentation with SegFormer on Drone Dataset. You can check out the blog on Medium You can also try out the model with
Aircraft design optimization made fast through modern automatic differentiation
Aircraft design optimization made fast through modern automatic differentiation. Plug-and-play analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more.
Stock-Prediction - prediction of stock market movements using sentiment analysis and deep learning.
Stock-Prediction- In this project, we aim to enhance the prediction of stock market movements using sentiment analysis and deep learning. We divide th
ALSPAC data analysis studying links between screen-usage and mental health issues in children. Provided data has been synthesised.
ADSMH - Mental Health and Screen Time Group coursework for Applied Data Science at the University of Bristol. Overview The data set that you have was
El Niño - Southern Oscillation analysis compared to minimum flow rates of rivers in northeast Brazil
ENSO (El Niño - Southern Oscillation) analysis in northeast Brazil É comprovada a influência dos fenômenos El Niño e La Niña nas secas no nordesde bra
EchoDNS - Analyze your DNS traffic super easy, shows all requested DNS traffic
EchoDNS - Analyze your DNS traffic super easy, shows all requested DNS traffic
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank
This repository provides the official code for replicating experiments from the paper: Semi-Supervised Semantic Segmentation with Pixel-Level Contrast
Labels4Free: Unsupervised Segmentation using StyleGAN
Labels4Free: Unsupervised Segmentation using StyleGAN ICCV 2021 Figure: Some segmentation masks predicted by Labels4Free Framework on real and synthet
This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures using receptive field analysis (RFA) and create graph visualizations of your architecture.
ReceptiveFieldAnalysisToolbox This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures usin
Liver segmentation using MONAI and pytorch
Machine Learning use case in the field of Healthcare. In this project MONAI and pytorch frameworks are used for 3D Liver segmentation.
Sentiment-Analysis and EDA on the IMDB Movie Review Dataset
Sentiment-Analysis and EDA on the IMDB Movie Review Dataset The main part of the work focuses on the exploration and study of different approaches whi
ioztat is a storage load analysis tool for OpenZFS
ioztat is a storage load analysis tool for OpenZFS. It provides iostat-like statistics at an individual dataset/zvol level.
A Python Bytecode Disassembler helping reverse engineers in dissecting Python binaries
A Python Bytecode Disassembler helping reverse engineers in dissecting Python binaries by disassembling and analyzing the compiled python byte-code(.pyc) files across all python versions (including Python 3.10.*)
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
PyPortfolioOpt has recently been published in the Journal of Open Source Software 🎉 PyPortfolioOpt is a library that implements portfolio optimizatio
Practical Machine Learning with Python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Semi-Automated Data Processing
Perform semi automated exploratory data analysis, feature engineering and feature selection on provided dataset by visualizing every possibilities on each step and assisting the user to make a meaningful decision to achieve a low-bias and low-variance model.
Retinal Vessel Segmentation with Pixel-wise Adaptive Filters (ISBI 2022)
Retinal Vessel Segmentation with Pixel-wise Adaptive Filters (ISBI 2022) Introdu
Security audit Python project dependencies against security advisory databases.
Security audit Python project dependencies against security advisory databases.
Exploratory Data Analysis of the 2019 Indian General Elections using a dataset from Kaggle.
2019-indian-election-eda Exploratory Data Analysis of the 2019 Indian General Elections using a dataset from Kaggle. This project is a part of the Cou
ICSS - Interactive Continual Semantic Segmentation
Presentation This repository contains the code of our paper: Weakly-supervised c
API Server for VoIP analysis (CDR + Audio CODECs)
Swagger generated server Overview This server was generated by the swagger-codegen project. By using the OpenAPI-Spec from a remote server, you can ea
AB-test-analyzer - Python class to perform AB test analysis
AB-test-analyzer Python class to perform AB test analysis Overview This repo con
Contains analysis of trends from Fitbit Dataset (source: Kaggle) to see how the trends can be applied to Bellabeat customers and Bellabeat products
Contains analysis of trends from Fitbit Dataset (source: Kaggle) to see how the trends can be applied to Bellabeat customers and Bellabeat products.
Repo for The Crown: Exploratory Analysis of Nim Malware DEF CON 615 talk
Repo for "The Crown: Exploratory Analysis of Nim Malware" DEF CON 615 talk
Official Implementation of ReferFormer
The official implementation of the paper: Language as Queries for Referring Video Object Segmentation Language as Queries for Referring Video Object S
Tackling the Class Imbalance Problem of Deep Learning Based Head and Neck Organ Segmentation
Info This is the code repository of the work Tackling the Class Imbalance Problem of Deep Learning Based Head and Neck Organ Segmentation from Elias T
Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis
Introduction This is an implementation of our paper Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis.
Orange Chicken: Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation
Orange Chicken: Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation This repository contains code and data f
City Surfaces: City-scale Semantic Segmentation of Sidewalk Surfaces
City Surfaces: City-scale Semantic Segmentation of Sidewalk Surfaces Paper Temporary GitHub page for City Surfaces paper. More soon! While designing s
HuSpaCy: industrial-strength Hungarian natural language processing
HuSpaCy: Industrial-strength Hungarian NLP HuSpaCy is a spaCy model and a library providing industrial-strength Hungarian language processing faciliti
Repository for the AugmentedPCA Python package.
Overview This Python package provides implementations of Augmented Principal Component Analysis (AugmentedPCA) - a family of linear factor models that
prior-based-losses-for-medical-image-segmentation
Repository for papers: Benchmark: Effect of Prior-based Losses on Segmentation Performance: A Benchmark Midl: A Surprisingly Effective Perimeter-based
A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband Items
A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband Items This repository co
Specification language for generating Generalized Linear Models (with or without mixed effects) from conceptual models
tisane Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships TL;DR: Analysts can use Tisane to author gener
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.
Language-Driven Semantic Segmentation
Language-driven Semantic Segmentation (LSeg) The repo contains official PyTorch Implementation of paper Language-driven Semantic Segmentation. Authors
Active Transport Analytics Model: A new strategic transport modelling and data visualization framework
{ATAM} Active Transport Analytics Model Active Transport Analytics Model (“ATAM”
YOLOX-CondInst - Implement CondInst which is a instances segmentation method on YOLOX
YOLOX CondInst -- YOLOX 实例分割 前言 本项目是自己学习实例分割时,复现的代码. 通过自己编程,让自己对实例分割有更进一步的了解。 若想
Active Transport Analytics Model (ATAM) is a new strategic transport modelling and data visualization framework for Active Transport as well as emerging micro-mobility modes
{ATAM} Active Transport Analytics Model Active Transport Analytics Model (“ATAM”) is a new strategic transport modelling and data visualization framew
Sentinel-1 SAR time series analysis for OSINT use
SARveillance Sentinel-1 SAR time series analysis for OSINT use. Description Generates a time lapse GIF of the Sentinel-1 satellite images for the loca
People tracker on the Internet: OSINT analysis and research tool by Jose Pino
trape (stable) v2.0 People tracker on the Internet: Learn to track the world, to avoid being traced. Trape is an OSINT analysis and research tool, whi
deep learning for image processing including classification and object-detection etc.
深度学习在图像处理中的应用教程 前言 本教程是对本人研究生期间的研究内容进行整理总结,总结的同时也希望能够帮助更多的小伙伴。后期如果有学习到新的知识也会与大家一起分享。 本教程会以视频的方式进行分享,教学流程如下: 1)介绍网络的结构与创新点 2)使用Pytorch进行网络的搭建与训练 3)使用Te
Always know what to expect from your data.
Great Expectations Always know what to expect from your data. Introduction Great Expectations helps data teams eliminate pipeline debt, through data t
Jupyter notebook and datasets from the pandas Q&A video series
Python pandas Q&A video series Read about the series, and view all of the videos on one page: Easier data analysis in Python with pandas. Jupyter Note
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
100 pandas puzzles Puzzles notebook Solutions notebook Inspired by 100 Numpy exerises, here are 100* short puzzles for testing your knowledge of panda
🙄 Difficult algorithm, Simple code.
🎉TensorFlow2.0-Examples🎉! "Talk is cheap, show me the code." ----- Linus Torvalds Created by YunYang1994 This tutorial was designed for easily divin
FMA: A Dataset For Music Analysis
FMA: A Dataset For Music Analysis Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson. International Society for Music Information
Python library for the analysis of dynamic measurements
Python library for the analysis of dynamic measurements The goal of this library is to provide a starting point for users in metrology and related are
Streamlit App For Product Analysis - Streamlit App For Product Analysis
Streamlit_App_For_Product_Analysis Здравствуйте! Перед вами дашборд, позволяющий
Delta Conformity Sociopatterns Analysis - Delta Conformity Sociopatterns Analysis
Delta_Conformity_Sociopatterns_Analysis ∆-Conformity is a local homophily measur
Practical Time-Series Analysis, published by Packt
Practical Time-Series Analysis This is the code repository for Practical Time-Series Analysis, published by Packt. It contains all the supporting proj
Greedy Gaussian Segmentation
GGS Greedy Gaussian Segmentation (GGS) is a Python solver for efficiently segmenting multivariate time series data. For implementation details, please
U-Time: A Fully Convolutional Network for Time Series Segmentation
U-Time & U-Sleep Official implementation of The U-Time [1] model for general-purpose time-series segmentation. The U-Sleep [2] model for resilient hig
Code from Daniel Lemire, A Better Alternative to Piecewise Linear Time Series Segmentation
PiecewiseLinearTimeSeriesApproximation code from Daniel Lemire, A Better Alternative to Piecewise Linear Time Series Segmentation, SIAM Data Mining 20
A simple flask application to collect annotations for the Turing Change Point Dataset, a benchmark dataset for change point detection algorithms
AnnotateChange Welcome to the repository of the "AnnotateChange" application. This application was created to collect annotations of time series data
Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)
taganomaly Anomaly detection labeling tool, specifically for multiple time series (one time series per category). Taganomaly is a tool for creating la
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection
Deep learning for time series forecasting Flow forecast is an open-source deep learning for time series forecasting framework. It provides all the lat
Survival analysis in Python
What is survival analysis and why should I learn it? Survival analysis was originally developed and applied heavily by the actuarial and medical commu
:spaghetti: Pastas is an open-source Python framework for the analysis of hydrological time series.
Pastas: Analysis of Groundwater Time Series Pastas: what is it? Pastas is an open source python package for processing, simulating and analyzing groun
(JMLR' 19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Python Outlier Detection (PyOD) Deployment & Documentation & Stats & License PyOD is a comprehensive and scalable Python toolkit for detecting outlyin
Hierarchical Time Series Forecasting with a familiar API
scikit-hts Hierarchical Time Series with a familiar API. This is the result from not having found any good implementations of HTS on-line, and my work
Technical Analysis library in pandas for backtesting algotrading and quantitative analysis
bta-lib - A pandas based Technical Analysis Library bta-lib is pandas based technical analysis library and part of the backtrader family. Links Main P
Highly comparative time-series analysis
〰️ hctsa 〰️ : highly comparative time-series analysis hctsa is a software package for running highly comparative time-series analysis using Matlab (fu
Timeseries analysis for neuroscience data
=================================================== Nitime: timeseries analysis for neuroscience data ===============================================