4872 Repositories
Python DNA-sequence-classification-by-Deep-Neural-Network Libraries
PyTorch META-DATASET (Few-shot classification benchmark)
PyTorch META-DATASET (Few-shot classification benchmark) This repo contains a PyTorch implementation of meta-dataset and a unified implementation of s
Spectral normalization (SN) is a widely-used technique for improving the stability and sample quality of Generative Adversarial Networks (GANs)
Why Spectral Normalization Stabilizes GANs: Analysis and Improvements [paper (NeurIPS 2021)] [paper (arXiv)] [code] Authors: Zinan Lin, Vyas Sekar, Gi
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Abstract Many applications of generative models rely on the marginali
Pairwise Learning for Neural Link Prediction for OGB (PLNLP-OGB)
Pairwise Learning for Neural Link Prediction for OGB (PLNLP-OGB) This repository provides evaluation codes of PLNLP for OGB link property prediction t
A hybrid framework (neural mass model + ML) for SC-to-FC prediction
The current workflow simulates brain functional connectivity (FC) from structural connectivity (SC) with a neural mass model. Gradient descent is applied to optimize the parameters in the neural mass model.
Neuralnetwork - Basic Multilayer Perceptron Neural Network for deep learning
Neural Network Just a basic Neural Network module Usage Example Importing Module
PcapConverter - A project for generating 15min frames out of a .pcap file containing network traffic
CMB Assignment 02 code + notebooks This is a project for containing code for the
E2EDNA2 - An automated pipeline for simulation of DNA aptamers complexed with small molecules and short peptides
E2EDNA2 - An automated pipeline for simulation of DNA aptamers complexed with small molecules and short peptides
This is a Deep Leaning API for classifying emotions from human face and human audios.
Emotion AI This is a Deep Leaning API for classifying emotions from human face and human audios. Starting the server To start the server first you nee
Predicting Auction Sale Price using the kaggle bulldozer auction sales data: Modeling with Ensembles vs Neural Network
Predicting Auction Sale Price using the kaggle bulldozer auction sales data: Modeling with Ensembles vs Neural Network The performances of tree ensemb
Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)
Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt) Task Training huge unsupervised deep neural networks yields to strong progress in
Sdf sparse conv - Deep Learning on SDF for Classifying Brain Biomarkers
Deep Learning on SDF for Classifying Brain Biomarkers To reproduce the results f
Pyspark sam - Analyze Big Sequence Alignments with PySpark in AWS EMR
pyspark_sam This repo hosts my code for the article "Analyze Big Sequence Alignm
Vit-ImageClassification - Pytorch ViT for Image classification on the CIFAR10 dataset
Vit-ImageClassification Introduction This project uses ViT to perform image clas
Labelbox is the fastest way to annotate data to build and ship artificial intelligence applications
Labelbox Labelbox is the fastest way to annotate data to build and ship artificial intelligence applications. Use this github repository to help you s
CVAT is free, online, interactive video and image annotation tool for computer vision
Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our
CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs
CLIP [Blog] [Paper] [Model Card] [Colab] CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pair
Simple and understandable swin-transformer OCR project
swin-transformer-ocr ocr with swin-transformer Overview Simple and understandable swin-transformer OCR project. The model in this repository heavily r
A library for benchmarking, developing and deploying deep learning anomaly detection algorithms
A library for benchmarking, developing and deploying deep learning anomaly detection algorithms Key Features • Getting Started • Docs • License Introd
Awesome Transformers in Medical Imaging
This repo supplements our Survey on Transformers in Medical Imaging Fahad Shamshad, Salman Khan, Syed Waqas Zamir, Muhammad Haris Khan, Munawar Hayat,
This code is for our paper "VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers"
ICCV Workshop 2021 VTGAN This code is for our paper "VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers"
Task Transformer Network for Joint MRI Reconstruction and Super-Resolution (MICCAI 2021)
T2Net Task Transformer Network for Joint MRI Reconstruction and Super-Resolution (MICCAI 2021) [Paper][Code] Dependencies numpy==1.18.5 scikit_image==
COVID-VIT: Classification of Covid-19 from CT chest images based on vision transformer models
COVID-ViT COVID-VIT: Classification of Covid-19 from CT chest images based on vision transformer models This code is to response to te MIA-COV19 compe
TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification
TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification [NeurIPS 2021] Abstract Multiple instance learn
Official repository for the ISBI 2021 paper Transformer Assisted Convolutional Neural Network for Cell Instance Segmentation
SegPC-2021 This is the official repository for the ISBI 2021 paper Transformer Assisted Convolutional Neural Network for Cell Instance Segmentation by
List of awesome things around semantic segmentation 🎉
Awesome Semantic Segmentation List of awesome things around semantic segmentation 🎉 Semantic segmentation is a computer vision task in which we label
Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks
Introduction This repository contains the modified caffe library and network architectures for our paper "Automated Melanoma Recognition in Dermoscopy
Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images
Lung Segmentation (2D) Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images. Demo See the application of the
Pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments
Cascaded-FCN This repository contains the pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments the liver and its lesions out of
Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network
ild-cnn This is supplementary material for the manuscript: "Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neur
Deep Learning to Improve Breast Cancer Detection on Screening Mammography
Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Deep Learning to Improve Breast
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA)
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis documents. Bibliography, experiments and reports.
Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification
Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification
Semantic Segmentation for Aerial Imagery using Convolutional Neural Network
This repo has been deprecated because whole things are re-implemented by using Chainer and I did refactoring for many codes. So please check this newe
Multiple Object Extraction from Aerial Imagery with Convolutional Neural Networks
This is an implementation of Volodymyr Mnih's dissertation methods on his Massachusetts road & building dataset and my original methods that are publi
Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets
Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets (including obl
This repository contains code, network definitions and pre-trained models for working on remote sensing images using deep learning
Deep learning for Earth Observation This repository contains code, network definitions and pre-trained models for working on remote sensing images usi
🛰️ Awesome Satellite Imagery Datasets
Awesome Satellite Imagery Datasets List of aerial and satellite imagery datasets with annotations for computer vision and deep learning. Newest datase
Learning to Segment Instances in Videos with Spatial Propagation Network
Learning to Segment Instances in Videos with Spatial Propagation Network This paper is available at the 2017 DAVIS Challenge website. Check our result
Source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree.
self-driving-car In this repository I will share the source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree. Hope this might
This is a Keras-based Python implementation of DeepMask- a complex deep neural network for learning object segmentation masks
NNProject - DeepMask This is a Keras-based Python implementation of DeepMask- a complex deep neural network for learning object segmentation masks. Th
Seg-Torch for Image Segmentation with Torch
Seg-Torch for Image Segmentation with Torch This work was sparked by my personal research on simple segmentation methods based on deep learning. It is
CN24 is a complete semantic segmentation framework using fully convolutional networks
Build status: master (production branch): develop (development branch): Welcome to the CN24 GitHub repository! CN24 is a complete semantic segmentatio
Segment axon and myelin from microscopy data using deep learning
Segment axon and myelin from microscopy data using deep learning. Written in Python. Using the TensorFlow framework. Based on a convolutional neural network architecture. Pixels are classified as either axon, myelin or background.
DeepCO3: Deep Instance Co-segmentation by Co-peak Search and Co-saliency
[CVPR19] DeepCO3: Deep Instance Co-segmentation by Co-peak Search and Co-saliency (Oral paper) Authors: Kuang-Jui Hsu, Yen-Yu Lin, Yung-Yu Chuang PDF:
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions
Natural Posterior Network This repository provides the official implementation o
Built a deep neural network (DNN) that functions as an end-to-end machine translation pipeline
Built a deep neural network (DNN) that functions as an end-to-end machine translation pipeline. The pipeline accepts english text as input and returns the French translation.
Code for the paper "Generative design of breakwaters usign deep convolutional neural network as a surrogate model"
Generative design of breakwaters usign deep convolutional neural network as a surrogate model This repository contains the code for the paper "Generat
A deep neural networks for images using CNN algorithm.
Example-CNN-Project This is a simple project showing how to implement deep neural networks using CNN algorithm. The dataset is taken from this link: h
Decision tree is the most powerful and popular tool for classification and prediction
Diabetes Prediction Using Decision Tree Introduction Decision tree is the most powerful and popular tool for classification and prediction. A Decision
To prepare an image processing model to classify the type of disaster based on the image dataset
Disaster Classificiation using CNNs bunnysaini/Disaster-Classificiation Goal To prepare an image processing model to classify the type of disaster bas
This project generates news headlines using a Long Short-Term Memory (LSTM) neural network.
News Headlines Generator bunnysaini/Generate-Headlines Goal This project aims to generate news headlines using a Long Short-Term Memory (LSTM) neural
Computer Vision is an elective course of MSAI, SCSE, NTU, Singapore
[AI6122] Computer Vision is an elective course of MSAI, SCSE, NTU, Singapore. The repository corresponds to the AI6122 of Semester 1, AY2021-2022, starting from 08/2021. The instructor of this course is Prof. Lu Shijian.
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch
NuPIC Studio is an all-in-one tool that allows users create a HTM neural network from scratch
NuPIC Studio is an all-in-one tool that allows users create a HTM neural network from scratch, train it, collect statistics, and share it among the members of the community. It is not just a visualization tool but an HTM builder, debugger and laboratory for experiments. It is ideal for newbies with little intimacy with NuPIC code as well as experts that wish a better productivity. Among its features and advantages:
Real life contra a deep learning project built using mediapipe and openc
real-life-contra Description A python script that translates the body movement into in game control. Welcome to all new real life contra a deep learni
An curated collection of awesome resources about networking in cybersecurity
An ongoing curated collection of awesome software, libraries, frameworks, talks & videos, best practices, learning tutorials and important practical resources about networking in cybersecurity
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images Histological Image Segmentation This
BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python
BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python. Some of the algorithms included are mor
Tutorials, examples, collections, and everything else that falls into the categories: pattern classification, machine learning, and data mining
**Tutorials, examples, collections, and everything else that falls into the categories: pattern classification, machine learning, and data mining.** S
Sentiment Classification using WSD, Maximum Entropy & Naive Bayes Classifiers
Sentiment Classification using WSD, Maximum Entropy & Naive Bayes Classifiers
This repository contains several jupyter notebooks to help users learn to use neon, our deep learning framework
neon_course This repository contains several jupyter notebooks to help users learn to use neon, our deep learning framework. For more information, see
Dive into Machine Learning
Dive into Machine Learning Hi there! You might find this guide helpful if: You know Python or you're learning it 🐍 You're new to Machine Learning You
TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow with breakpoints + real-time visualization of the data flowing through the computational graph
TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow (Google's Deep Learning framework) with breakpoints + real-time visualization of the data flowing through the computational graph.
nn_builder lets you build neural networks with less boilerplate code
nn_builder lets you build neural networks with less boilerplate code. You specify the type of network you want and it builds it. Install pip install n
Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm
Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm
TResNet: High Performance GPU-Dedicated Architecture
TResNet: High Performance GPU-Dedicated Architecture paperV2 | pretrained models Official PyTorch Implementation Tal Ridnik, Hussam Lawen, Asaf Noy, I
IPV4 network calculation project in Python
Curso de Python 3 do Básico ao Avançado Desafio: Calculando redes IPV4 Criar um programa que obtem um numero de IP com o prefixo da mascara de rede. O
sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code
sequitur sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code. It implements three differ
This is an open solution to the Home Credit Default Risk challenge 🏡
Home Credit Default Risk: Open Solution This is an open solution to the Home Credit Default Risk challenge 🏡 . More competitions 🎇 Check collection
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently This repository is the official implementat
Google AI Open Images - Object Detection Track: Open Solution
Google AI Open Images - Object Detection Track: Open Solution This is an open solution to the Google AI Open Images - Object Detection Track 😃 More c
TGS Salt Identification Challenge
TGS Salt Identification Challenge This is an open solution to the TGS Salt Identification Challenge. Note Unfortunately, we can no longer provide supp
Airbus Ship Detection Challenge
Airbus Ship Detection Challenge This is an open solution to the Airbus Ship Detection Challenge. Our goals We are building entirely open solution to t
Image Classification - A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches
A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches
Land Cover Classification Random Forest
You can perform Land Cover Classification on Satellite Images using Random Forest and visualize the result using Earthpy package. Make sure to install the required packages and such as
Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution
Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution Figure: Example visualization of the method and baseline as a
Fast Differentiable Matrix Sqrt Root
Official Pytorch implementation of ICLR 22 paper Fast Differentiable Matrix Square Root
Open solution to the Toxic Comment Classification Challenge
Starter code: Kaggle Toxic Comment Classification Challenge More competitions 🎇 Check collection of public projects 🎁 , where you can find multiple
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents [Project Page] [Paper] [Video] Wenlong Huang1, Pieter Abbee
Deep Learning Topics with Computer Vision & NLP
Deep learning Udacity Course Deep Learning Topics with Computer Vision & NLP for the AWS Machine Learning Engineer Nanodegree Program Tasks are mostly
Deep Learning for Morphological Profiling
Deep Learning for Morphological Profiling An end-to-end implementation of a ML System for morphological profiling using self-supervised learning to di
This project has Classification and Clustering done Via kNN and K-Means respectfully
This project has Classification and Clustering done Via kNN and K-Means respectfully. It later tests its efficiency via F1/accuracy/recall/precision for kNN and Davies-Bouldin Index for Clustering. The Data is also visually represented.
ThorFI: A Novel Approach for Network Fault Injection as a Service
ThorFI: a Novel Approach for Network Fault Injection as a Service This repo includes ThorFI, a novel fault injection solution for virtual networks in
This Deep Learning Model Predicts that from which disease you are suffering.
Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int
Titanic Traveller Survivability Prediction
The aim of the mini project is predict whether or not a passenger survived based on attributes such as their age, sex, passenger class, where they embarked and more.
Neural Machine Translation (NMT) tutorial with OpenNMT-py
Neural Machine Translation (NMT) tutorial with OpenNMT-py. Data preprocessing, model training, evaluation, and deployment.
Binary Classification Problem with Machine Learning
Binary Classification Problem with Machine Learning Solving Approach: 1) Ultimate Goal of the Assignment: This assignment is about solving a binary cl
GNES enables large-scale index and semantic search for text-to-text, image-to-image, video-to-video and any-to-any content form
GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network.
Grover is a model for Neural Fake News -- both generation and detectio
Grover is a model for Neural Fake News -- both generation and detection. However, it probably can also be used for other generation tasks.
Transformer in Vision
Transformer-in-Vision Recent Transformer-based CV and related works. Welcome to comment/contribute! Keep updated. Resource SCENIC: A JAX Library for C
A curated list of efficient attention modules
awesome-fast-attention A curated list of efficient attention modules
Full Transformer Framework for Robust Point Cloud Registration with Deep Information Interaction
Full Transformer Framework for Robust Point Cloud Registration with Deep Information Interaction. arxiv This repository contains python scripts for tr
Learning to Prompt for Continual Learning
Learning to Prompt for Continual Learning (L2P) Official Jax Implementation L2P is a novel continual learning technique which learns to dynamically pr
Tree Nested PyTorch Tensor Lib
DI-treetensor treetensor is a generalized tree-based tensor structure mainly developed by OpenDILab Contributors. Almost all the operation can be supp
FSL-Mate: A collection of resources for few-shot learning (FSL).
FSL-Mate is a collection of resources for few-shot learning (FSL). In particular, FSL-Mate currently contains FewShotPapers: a paper list which tracks
ECLARE: Extreme Classification with Label Graph Correlations
ECLARE ECLARE: Extreme Classification with Label Graph Correlations @InProceedings{Mittal21b, author = "Mittal, A. and Sachdeva, N. and Agrawal
GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification
GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,
Official code repository for the work: "The Implicit Values of A Good Hand Shake: Handheld Multi-Frame Neural Depth Refinement"
Handheld Multi-Frame Neural Depth Refinement This is the official code repository for the work: The Implicit Values of A Good Hand Shake: Handheld Mul