8583 Repositories
Python table-detection-using-deep-learning Libraries
Machine-learning-dell - Repositório com as atividades desenvolvidas no curso de Machine Learning
📚 Descrição Neste curso da Dell aprofundamos nossos conhecimentos em Machine Learning. 🖥️ Aulas (Em curso) 1.1 - Python aplicado a Data Science 1.2
House_prices_kaggle - Predict sales prices and practice feature engineering, RFs, and gradient boosting
House Prices - Advanced Regression Techniques Predicting House Prices with Machine Learning This project is build to enhance my knowledge about machin
BRNet - code for Automated assessment of BI-RADS categories for ultrasound images using multi-scale neural networks with an order-constrained loss function
BRNet code for "Automated assessment of BI-RADS categories for ultrasound images using multi-scale neural networks with an order-constrained loss func
CS_Final_Metal_surface_detection - This is a final project for CoderSchool Machine Learning bootcamp on 29/12/2021.
CS_Final_Metal_surface_detection This is a final project for CoderSchool Machine Learning bootcamp on 29/12/2021. The project is based on the dataset
StyleGAN2-ADA-training-jupyter - Training custom datasets in styleGAN2-ADA by NVIDIA using Jupyter
styleGAN2-ADA-training-jupyter Training custom datasets in styleGAN2-ADA on Jupyter Official StyleGAN2-ADA by NIVIDIA Paper Training Generative Advers
Breast Cancer Detection 🔬 ITI "AI_Pro" Graduation Project
BreastCancerDetection - This program is designed to predict two severity of abnormalities associated with breast cancer cells: benign and malignant. Mammograms from MIAS is preprocessed and features are extracted using the pre-trained CNN.
Faza - Faza terminal, Faza help to beginners for pen testing
Faza terminal simple tool for pen testers Use small letter only for commands Don't use space after command 'help' for more information Installation gi
Youtube_dl_helper - A hacky python script meant to automate the process of downloading mp3 files from YouTube using youtube-dl library
youtube_dl_helper A helper program meant to automate the process of downloading mp3 files from YouTube using youtube-dl library Dependencies In order
Ghdl-interactive-sim - Interactive GHDL simulation of a VHDL adder using Python, Cocotb, and pygame
GHDL Interactive Simulation This is an interactive test bench for a simple VHDL adder. It uses GHDL to elaborate/run the simulation. It is coded in Py
Codeflare - Scale complex AI/ML pipelines anywhere
Scale complex AI/ML pipelines anywhere CodeFlare is a framework to simplify the integration, scaling and acceleration of complex multi-step analytics
CS5242_2021 - Neural Networks and Deep Learning, NUS CS5242, 2021
CS5242_2021 Neural Networks and Deep Learning, NUS CS5242, 2021 Cloud Machine #1 : Google Colab (Free GPU) Follow this Notebook installation : https:/
VQMIVC - Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversion
VQMIVC: Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversion (Interspeech
Generating .npy dataset and labels out of given image, containing numbers from 0 to 9, using opencv
basic-dataset-generator-from-image-of-numbers generating .npy dataset and labels out of given image, containing numbers from 0 to 9, using opencv inpu
ToDoListAndroid - To-do list application created using Kivymd
ToDoListAndroid To-do list application created using Kivymd. Version 1.0.0 (1/Jan/2022). Planned to do next: -Add setting (theme selector, etc) -Add f
Houseprices - Predict sales prices and practice feature engineering, RFs, and gradient boosting
House Prices - Advanced Regression Techniques Predicting House Prices with Machine Learning This project is build to enhance my knowledge about machin
Training Cifar-10 Classifier Using VGG16
opevcvdl-hw3 This project uses pytorch and Qt to achieve the requirements. Version Python 3.6 opencv-contrib-python 3.4.2.17 Matplotlib 3.1.1 pyqt5 5.
Image Processing, Image Smoothing, Edge Detection and Transforms
opevcvdl-hw1 This project uses openCV and Qt to achieve the requirements. Version Python 3.7 opencv-contrib-python 3.4.2.17 Matplotlib 3.1.1 pyqt5 5.1
Air Quality Prediction Using LSTM
AirQualityPredictionUsingLSTM In this Repo, i present to you the winning solution of smart gujarat hackathon 2019 where the task was to predict the qu
Statistical Rethinking: A Bayesian Course Using CmdStanPy and Plotnine
Statistical Rethinking: A Bayesian Course Using CmdStanPy and Plotnine Intro This repo contains the python/stan version of the Statistical Rethinking
TwitterDataStreaming - Twitter data streaming using APIs
Twitter_Data_Streaming Twitter data streaming using APIs Use Case 1: Streaming r
PythonCalculator - A simple Calculator made in python using tkinter for GUI
PythonCalculator A simple Calculator made in python using tkinter for GUI. For P
Gesture-Volume-Control - This Python program can adjust the system's volume by using hand gestures
Gesture-Volume-Control This Python program can adjust the system's volume by usi
Sample-fastapi - A sample app using Fastapi that you can deploy on App Platform
Getting Started We provide a sample app using Fastapi that you can deploy on App
MultiTaskLearning - Multi Task Learning for 3D segmentation
Multi Task Learning for 3D segmentation Perception stack of an Autonomous Drivin
Apriori - An algorithm for frequent item set mining and association rule learning over relational databases
Apriori Apriori is an algorithm for frequent item set mining and association rul
HAR-stacked-residual-bidir-LSTMs - Deep stacked residual bidirectional LSTMs for HAR
HAR-stacked-residual-bidir-LSTM The project is based on this repository which is presented as a tutorial. It consists of Human Activity Recognition (H
Clean Machine Learning, a Coding Kata
Kata: Clean Machine Learning From Dirty Code First, open the Kata in Google Colab (or else download it) You can clone this project and launch jupyter-
Neural-fractal - Create Fractals Using Complex-Valued Neural Networks!
Neural Fractal Create Fractals Using Complex-Valued Neural Networks! Home Page Features Define Dynamical Systems Using Complex-Valued Neural Networks
LQM - Improving Object Detection by Estimating Bounding Box Quality Accurately
Improving Object Detection by Estimating Bounding Box Quality Accurately Abstract Object detection aims to locate and classify object instances in ima
Resmed_myair_sensors - This is a Home Assistant custom component to pull daily CPAP data from ResMed's myAir service using an undocumented API
resmed_myair This component will set up the following platforms. Platform Description sensor Show info from the myAir API. Installation Using the tool
Image-Stitching - Panorama composition using SIFT Features and a custom implementaion of RANSAC algorithm
About The Project Panorama composition using SIFT Features and a custom implementaion of RANSAC algorithm (Random Sample Consensus). Author: Andreas P
JudeasRx - graphical app for doing personalized causal medicine using the methods invented by Judea Pearl et al.
JudeasRX Instructions Read the references given in the Theory and Notation section below Fire up the Jupyter Notebook judeas-rx.ipynb The notebook dra
Discord-Bot - Bot using nextcord for beginners
Discord-Bot Bot using nextcord for beginners! Requirements: 1 :- Install nextcord by typing "pip install nextcord" Thats it! You can use this code any
Get-Phone-Number-Details-using-Python - To get the details of any number, we can use an amazing Python module known as phonenumbers.
Get-Phone-Number-Details-using-Python To get the details of any number, we can use an amazing Python module known as phonenumbers. We can use the amaz
Iris-Heroku - Putting a Machine Learning Model into Production with Flask and Heroku
Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L
Face_mosaic - Mosaic blur processing is applied to multiple faces appearing in the video
動機 face_recognitionを使用して得られる顔座標は長方形であり、この座標をそのまま用いてぼかし処理を行った場合得られる画像は醜い。 それに対してモ
42-event-notifier - 42 Event notifier using 42API and Github Actions
42 Event Notifier 42서울 Agenda에 새로운 이벤트가 등록되면 알려드립니다! 현재는 Github Issue로 등록되므로 상단
A Survey on Deep Learning Technique for Video Segmentation
A Survey on Deep Learning Technique for Video Segmentation A Survey on Deep Learning Technique for Video Segmentation Wenguan Wang, Tianfei Zhou, Fati
SOTA easy to use PyTorch-based DL training library
Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open
Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible
IMBENS: Class-imbalanced Ensemble Learning in Python Language: English | Chinese/中文 Links: Documentation | Gallery | PyPI | Changelog | Source | Downl
streamlit translator is used to detect and translate between languages created using gTTS, googletrans, pillow and streamlit python packages
Streamlit Translator Streamlit Translator is a simple translator app to detect and translate between languages. Streamlit Translator gets text and lan
AI-generated-characters for Learning and Wellbeing
AI-generated-characters for Learning and Wellbeing Click here for the full project page. This repository contains the source code for the paper AI-gen
PyTorch Lightning + Hydra. A feature-rich template for rapid, scalable and reproducible ML experimentation with best practices. ⚡🔥⚡
Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re
Natural Language Processing for Adverse Drug Reaction (ADR) Detection
Natural Language Processing for Adverse Drug Reaction (ADR) Detection This repo contains code from a project to identify ADRs in discharge summaries a
A library for uncertainty quantification based on PyTorch
Torchuq [logo here] TorchUQ is an extensive library for uncertainty quantification (UQ) based on pytorch. TorchUQ currently supports 10 representation
The codebase for Data-driven general-purpose voice activity detection.
Data driven GPVAD Repository for the work in TASLP 2021 Voice activity detection in the wild: A data-driven approach using teacher-student training. S
The official MegEngine implementation of the ICCV 2021 paper: GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning
[ICCV 2021] GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning This is the official implementation of our ICCV2021 paper GyroFlow. Our pres
Official PyTorch implementation of "Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble" (NeurIPS'21)
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble This is the code for reproducing the results of the paper Uncertainty-Bas
WaveFake: A Data Set to Facilitate Audio DeepFake Detection
WaveFake: A Data Set to Facilitate Audio DeepFake Detection This is the code repository for our NeurIPS 2021 (Track on Datasets and Benchmarks) paper
The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.
Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode
Bulk2Space is a spatial deconvolution method based on deep learning frameworks
Bulk2Space Spatially resolved single-cell deconvolution of bulk transcriptomes using Bulk2Space Bulk2Space is a spatial deconvolution method based on
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
A state-of-the-art semi-supervised method for image recognition
Mean teachers are better role models Paper ---- NIPS 2017 poster ---- NIPS 2017 spotlight slides ---- Blog post By Antti Tarvainen, Harri Valpola (The
Ladder network is a deep learning algorithm that combines supervised and unsupervised learning
This repository contains source code for the experiments in a paper titled Semi-Supervised Learning with Ladder Networks by A Rasmus, H Valpola, M Hon
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object Segmentation.
Training Script for Reuse-VOS This code implementation of CVPR 2021 paper : Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Vi
Code used for the results in the paper "ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning"
Code used for the results in the paper "ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning" Getting started Prerequisites CUD
A simple consistency training framework for semi-supervised image semantic segmentation
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation PseudoSeg is a simple consistency training framework for semi-supervised image semantic s
A PyTorch-based Semi-Supervised Learning (SSL) Codebase for Pixel-wise (Pixel) Vision Tasks
PixelSSL is a PyTorch-based semi-supervised learning (SSL) codebase for pixel-wise (Pixel) vision tasks. The purpose of this project is to promote the
Learning Saliency Propagation for Semi-supervised Instance Segmentation
Learning Saliency Propagation for Semi-supervised Instance Segmentation PyTorch Implementation This repository contains: the PyTorch implementation of
Semi-Supervised Semantic Segmentation with Cross-Consistency Training (CCT)
Semi-Supervised Semantic Segmentation with Cross-Consistency Training (CCT) Paper, Project Page This repo contains the official implementation of CVPR
CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing
CapsuleVOS This is the code for the ICCV 2019 paper CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing. Arxiv Link: https://a
Code for Universal Semi-Supervised Semantic Segmentation models paper accepted in ICCV 2019
USSS_ICCV19 Code for Universal Semi Supervised Semantic Segmentation accepted to ICCV 2019. Full Paper available at https://arxiv.org/abs/1811.10323.
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations, CVPR 2019 (Oral)
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations The code of: Weakly Supervised Learning of Instance Segmentation with I
Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018
Adversarial Learning for Semi-supervised Semantic Segmentation This repo is the pytorch implementation of the following paper: Adversarial Learning fo
Weakly- and Semi-Supervised Panoptic Segmentation (ECCV18)
Weakly- and Semi-Supervised Panoptic Segmentation by Qizhu Li*, Anurag Arnab*, Philip H.S. Torr This repository demonstrates the weakly supervised gro
Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR 2018).
Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR2018) By Zilong Huang, Xinggang Wang, Jiasi Wang, Wenyu Liu and J
Weakly Supervised Segmentation by Tensorflow.
Weakly Supervised Segmentation by Tensorflow. Implements semantic segmentation in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).
Implementation of " SESS: Self-Ensembling Semi-Supervised 3D Object Detection" (CVPR2020 Oral)
SESS: Self-Ensembling Semi-Supervised 3D Object Detection Created by Na Zhao from National University of Singapore Introduction This repository contai
Semi-supervised learning for object detection
Source code for STAC: A Simple Semi-Supervised Learning Framework for Object Detection STAC is a simple yet effective SSL framework for visual object
Weakly-supervised object detection.
Wetectron Wetectron is a software system that implements state-of-the-art weakly-supervised object detection algorithms. Project CVPR'20, ECCV'20 | Pa
CSD: Consistency-based Semi-supervised learning for object Detection
CSD: Consistency-based Semi-supervised learning for object Detection (NeurIPS 2019) By Jisoo Jeong, Seungeui Lee, Jee-soo Kim, Nojun Kwak Installation
Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.
COResets and Data Subset selection Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order
PyTorch implementation of Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose
Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose Release Notes The official PyTorch implementation of Neural View S
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval, CVPR 2021. Ayan Kumar Bhunia, Pinaki nath Chowdh
[CVPR'2020] DeepDeform: Learning Non-rigid RGB-D Reconstruction with Semi-supervised Data
DeepDeform (CVPR'2020) DeepDeform is an RGB-D video dataset containing over 390,000 RGB-D frames in 400 videos, with 5,533 optical and scene flow imag
Image to Image translation, image generataton, few shot learning
Semi-supervised Learning for Few-shot Image-to-Image Translation [paper] Abstract: In the last few years, unpaired image-to-image translation has witn
A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.
Deep SAD: A Method for Deep Semi-Supervised Anomaly Detection This repository provides a PyTorch implementation of the Deep SAD method presented in ou
Learning to Self-Train for Semi-Supervised Few-Shot
Learning to Self-Train for Semi-Supervised Few-Shot Classification This repository contains the TensorFlow implementation for NeurIPS 2019 Paper "Lear
A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised Learning
LABES This is the code for EMNLP 2020 paper "A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised L
MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification
MixText This repo contains codes for the following paper: Jiaao Chen, Zichao Yang, Diyi Yang: MixText: Linguistically-Informed Interpolation of Hidden
Datasets for new state-of-the-art challenge in disentanglement learning
High resolution disentanglement datasets This repository contains the Falcor3D and Isaac3D datasets, which present a state-of-the-art challenge for co
implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning"
MarginGAN This repository is the implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning". 1."preliminary" is the imp
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model Baris Gecer 1, Binod Bhattarai 1
Good Semi-Supervised Learning That Requires a Bad GAN
Good Semi-Supervised Learning that Requires a Bad GAN This is the code we used in our paper Good Semi-supervised Learning that Requires a Bad GAN Ziha
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning Source code for AISTATS 2019 paper: Confidence-based Graph Convolutional Ne
Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs
Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs MATLAB implementation of the paper: P. Mercado, F. Tudisco, and M. Hein,
Training neural models with structured signals.
Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured
Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Learning with Nonignorable Nonresponses‘
Graph-based joint model with Nonignorable Missingness (GNM) This is a Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Lear
A Flexible Generative Framework for Graph-based Semi-supervised Learning (NeurIPS 2019)
G3NN This repo provides a pytorch implementation for the 4 instantiations of the flexible generative framework as described in the following paper: A
Meta Learning for Semi-Supervised Few-Shot Classification
few-shot-ssl-public Code for paper Meta-Learning for Semi-Supervised Few-Shot Classification. [arxiv] Dependencies cv2 numpy pandas python 2.7 / 3.5+
Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
Semi-supervised Deep Kernel Learning This is the code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data
Scaling and Benchmarking Self-Supervised Visual Representation Learning
FAIR Self-Supervision Benchmark is deprecated. Please see VISSL, a ground-up rewrite of benchmark in PyTorch. FAIR Self-Supervision Benchmark This cod
Joint Unsupervised Learning (JULE) of Deep Representations and Image Clusters.
Joint Unsupervised Learning (JULE) of Deep Representations and Image Clusters. Overview This project is a Torch implementation for our CVPR 2016 paper
PyTorch implementation for Graph Contrastive Learning with Augmentations
Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*
CCCL: Contrastive Cascade Graph Learning.
CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr
ViberExport - Export messages from Viber messenger using viber.db file
📲 ViberExport Export messages from Viber messenger using viber.db file ⚡ Usage:
This is a scalable system that reads messages from public Telegram channels using Telethon and stores the data in a PostgreSQL database.
This is a scalable system that reads messages from public Telegram channels using Telethon and stores the data in a PostgreSQL database. Its original intention is to monitor cryptocurrency related channels, but it can be configured to read any Telegram data that is accessible through the API.
Memory-efficient optimum einsum using opt_einsum planning and PyTorch kernels.
opt-einsum-torch There have been many implementations of Einstein's summation. numpy's numpy.einsum is the least efficient one as it only runs in sing
⭐️ Pyro String Generator ⭐️ Genrate String Session Using this bot.Made by TeamUltronX 🔥
⭐️ Pyro String Generator ⭐️ Genrate String Session Using this bot.Made by TeamUltronX 🔥 Configs: API_HASH Get from Here. API_ID Get from Here. API_KE