머신러닝 · GitHub

Official code for Cotatron @ INTERSPEECH 2020

OCR, Archive, Index and Search: Implementation agnostic OCR framework.

Learning and Building Convolutional Neural Networks using PyTorch

A tool for efficient semi-supervised video object segmentation (great results with minimal manual labor) and a dataset for benchmarking

a repo sharing Bayesian Neural Network recent papers

Auto-Annotate - Automatically annotate your entire image directory by a single command. As simple as saying - "Annotate all the street sign (label) in the autonomous car dataset (directory)" and BAM! DONE. Each and every image with a street sign in the diverse dataset directory containing images of all sorts which have a street sign are filtered and the segmentation annotation is performed in a single command. The Auto-Annotate tool provides auto annotation of segmentation masks for the objects in the images inside some directory based on the labels. Auto-Annotate is able to provide automated annotations for the labels defined in the COCO Dataset and also supports Custom Labels.

Feature Books for Machine Learning

Plant Disease Detection is one of the mind-boggling issues when we talk about using Technology in Agriculture. Although researches have been done to detect whether a plant is healthy or diseased using Deep Learning and with the help of Neural Network, new techniques are still being discovered. For Fewer Data Classical Machine Learning Models are said to outstand given the data is pre-processed well. On the same theory here is my approach for Detecting whether a plant leaf is healthy or unhealthy by utilizing the classical Machine Learning Models, Pre-processing the Image Data. The data was fed to 7 Machine Learning Models with 10 fold cross-validation out of which Random Forest Classifier outperformed all the other models giving an accuracy of 97% on the test set.

A Complete and Simple Implementation of MobileNet-V2 in PyTorch

Code of paper "Deep Learning Classifiers for Hyperspectral Imaging: A Review"

Deep learning models for remote sensing applications

Multi-Person Pose Estimation project for Tensorflow 2.0 with a small and fast model based on MobilenetV3

Video Platform for Action Recognition and Object Detection in Pytorch

This is the implementation of CVPR2020 paper “Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition”.

PyTorch Code for Neural MP: A Generalist Neural Motion Planner

study resources of model and engineering

Deep learning superresolution in pure rust

Official implementation of Neural Audio Fingerprint (ICASSP 2021)

GraphXAI: Resource to support the development and evaluation of GNN explainers

Subgraph Neural Networks (NeurIPS 2020)

Pytorch implementation for Semantic Segmentation with multi models (Deeplabv3, Deeplabv3_plus, PSPNet, UNet, UNet_AutoEncoder, UNet_nested, R2AttUNet, AttentionUNet, RecurrentUNet,, SEGNet, CENet, DsenseASPP, RefineNet, RDFNet)

A repository containing 300D character embeddings derived from the GloVe 840B/300D dataset, and uses these embeddings to train a deep learning model to generate Magic: The Gathering cards using Keras