Pinned Repositories
awesome-tv
국립국어원은 어쩔tv의 순화어로 'awesome-tv'를 제시했습니다.
book-forest
🌳 책숲 : 책들이 모여 숲을 이루는 장소
Dutch
중간 지점 탐색 어플 @ 세종대 프로그래밍 동아리 인터페이스
paper-notes
이슈로 가볍게 남깁니다.
S2R
Speech 2motion Recognition 🐹🐰
sjuce
학고 가이드
toolbox
⛏⛏⛏
uhhyunjoo's Repositories
uhhyunjoo/book-forest
🌳 책숲 : 책들이 모여 숲을 이루는 장소
uhhyunjoo/toolbox
⛏⛏⛏
uhhyunjoo/paper-notes
이슈로 가볍게 남깁니다.
uhhyunjoo/alro923.github.io
uhhyunjoo/augemented-analysis-for-industrial-data
Development of automatic data semantic information composition/expression technology based on augmented analysis for diagnosing industrial data status and maximizing improvement
uhhyunjoo/cat-jjal-maker-workshop
uhhyunjoo/CoMPM
Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in Conversation (NAACL 2022)
uhhyunjoo/cv
uhhyunjoo/ETRI-trajectory-analysis
Development of vehicle trajectory prediction and classification technology affecting traffic congestion, an ETRI commissioned research project
uhhyunjoo/flutter-practice
uhhyunjoo/git-training
:octocat: Don't think about git, just do git
uhhyunjoo/goProject
uhhyunjoo/hyun-boggle
현주가 포크 뜸
uhhyunjoo/IF_CleanCode
인터페이스 클린코드 스터디
uhhyunjoo/infcon2022-guestbook
🎉 INFCON 2022에 참여하신 분들의 방명록입니다.
uhhyunjoo/interface-retrospective
세종대학교 프로그래밍 동아리 인터페이스 회원들의 회고 모음
uhhyunjoo/level1-bookratingprediction-recsys-04
level1-bookratingprediction-recsys-04 created by GitHub Classroom
uhhyunjoo/lightning
The most intuitive, flexible, way for researchers, ML engineers and data scientists to build models (with PyTorch) and ML systems for the ML lifecycle with an obsessive focus on flexibility and performance.
uhhyunjoo/MeeatNow
uhhyunjoo/model-soups
uhhyunjoo/MonitoRSS-Clone
Repo to deploy the news-delivering bot MonitoRSS (formerly known as Discord.RSS)
uhhyunjoo/ossca-tutorial
uhhyunjoo/pytorch-example
uhhyunjoo/react-practice
연습중
uhhyunjoo/sp_tool
Smooth pursuit detection tool for eye tracking recordings
uhhyunjoo/streamlit-recsys
uhhyunjoo/test
uhhyunjoo/toybox
uhhyunjoo/uhhyunjoo
uhhyunjoo/VAE-LSTM-for-anomaly-detection
We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series.