2021 DIML Graduation Research Dashboard
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2021 DIML Graduation Research Dashboard
재미있는 연구 함께 해보아요!
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이름
날짜
환영합니다! - 연구참여확약서, 기초강의 리스트
Open
2021/07/08
졸업연구 진행 계획
Open
2021/07/08
COUNT
2
Phase 1
Deep Learning Basics
Phase 2
Deep Learning with Satellite Segmentation
Phase 3
Coding and Experiments
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Seminars
이름
태그
Phase
세미나 날짜
8월 1주차: Object Detection: 1-stage
Open
Object Detection
Phase 1
2021/08/04
Paper Seminar Lists
Open
7월 4주차 : Classification
Open
Object Classification
Phase 1
2021/07/21
7월 5주차: Object Detection: 2-stage
Open
Object Detection
Phase 1
2021/07/28
8월 2주차: Semantic Image Segmentation
Open
Segmentation
Phase 1
2021/08/11
8월 4주차: Satellite Segmentation
Open
Satellite Segmentation
Phase 2
2021/08/25
8월 3주차: GAN
Open
GAN
Phase 1
2021/08/18
9월 1주차: Coding U-Net
Open
Segmentation
Phase 2
2021/09/01
9월 2주차: Mirror Segmentation
Open
Segmentation
Phase 2
2021/09/08
9월 3주차: Transparent Segmentation
Open
Segmentation
Phase 2
2021/09/15
9월 4주차: SpaceNetChallenge Review
Open
Satellite Segmentation
Phase 2
2021/09/29
10월 1주차: Eo-Augmented SAR Segmentation
Open
Satellite Segmentation
Phase 2
2021/10/08
10월 2주차: 중간고사 휴강
Open
10월 3주차: Paper Seminar and Experiment Basic I
Open
Experiment
Phase 3
2021/10/22
10월 4주차: Paper Seminar and Experiment Basic II
Open
Experiment
Phase 3
2021/10/27
11월 1주차: Paper Seminar and Experiment Advance I
Open
Experiment
Phase 3
2021/11/03
11월 2주차: Paper Seminar and Experiment Advance II
Open
Experiment
Phase 3
2021/11/10
11월 3주차: Paper Seminar and Experiment Advance III
Open
Experiment
Phase 3
2021/11/17
11월 4주차: Evaluation and Metrics
Open
Experiment
Phase 3
2021/11/24
COUNT
19
갤러리 보기
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딥러닝 기초 (한글)
2. 딥러닝 기본 (영어)
모든 추천강의 리스트:
추천 기초강의 목록
GitHub - eungbean/Docker-for-AI-Researcher
"Docker for A.I. Researcher" is a series of Shell script that allows you to quickly set up your deep learning research environment. supports the next-generation pytorch library, pytorch-lightning. supports SSH! Remote work with laptop OUTSIDE of the box. includes fancy terminal setup with oh-my-zsh.
Docker-for-AI-Researchers