- Seoul, Korea
-
11:28
(UTC +09:00) - hyeok-jong.github.io
Lists (2)
Sort Name ascending (A-Z)
Stars
State-of-the-art retinal vessel segmentation with minimalistic models
A feature-rich command-line audio/video downloader
A lightweight, dependency-free Python library (and command-line utility) for downloading YouTube Videos.
Low code platform for building business apps and workflows in minutes. Supports PostgreSQL, MySQL, MariaDB, MSSQL, MongoDB, Rest API, Docker, K8s, and more 🚀
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
rPPG-Toolbox: Deep Remote PPG Toolbox (NeurIPS 2023)
A rPPG Strong Baseline for remote physiological measurement.
A complete computer science study plan to become a software engineer.
RETFound - A foundation model for retinal image
Based on the Pytorch-Transformers library by HuggingFace. To be used as a starting point for employing Transformer models in text classification tasks. Contains code to easily train BERT, XLNet, Ro…
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
A shortcode for Hugo(https://gohugo.io/) which allows you to embed a PDF file in a page using Pdf.js (https://mozilla.github.io/pdf.js/)
Official Code Repository for the paper "Grid Diffusion Models for Text-to-Video Generation", CVPR 2024
We present a comprehensive and deep review of the HFM in challenges, opportunities, and future directions. The released paper: https://arxiv.org/abs/2404.03264
NeurIPS2023 - A generic biosignal learning framework. Large EEG pre-trained models.
The pytorch implementation of our CVPR 2023 paper "Conditional Image-to-Video Generation with Latent Flow Diffusion Models"
Generative Adversarial Networks : paper, pytorch-code, review(Korean)
Code for the paper "Neuro-GPT: Towards a Foundation Model for EEG"
Code for extracting meta data from TUH EGG corpuses and queries
Deep learning software to decode EEG, ECG or MEG signals
selfEEG: a Python library for Self-Supervised Learning on Electroencephalography (EEG) data