서정훈

서정훈은 한국의 위성/항공 이미지 분석 회사인 SI Analytics의 연구 센터 기술 책임자입니다. 동시에 KAIST HCI Tech Lab (지도교수: 윤상호 교수)에서 석사과정 중에 있습니다. 주요 업무 범위는 원격 탐사 응용을 위한 컴퓨터 비전 및 기계 학습에 대한 연구 프로젝트를 지원하고 관리하는 것입니다. 그 외에도 컴퓨터 그래픽스, 병렬 컴퓨팅, 그리고 인간-컴퓨터 상호 작용을 위한 지능형 센싱 기술 등에 관심이 있으며 유관 경험이 있습니다.

전문 분야

• 머신러닝, 컴퓨터 비전, 컴퓨터 그래픽스, 그리고 이의 원격 탐사로의 응용
• 고성능컴퓨팅에서의 병렬 컴퓨팅 및 GPGPU
• 인간-컴퓨터 상호작용을 위한 지능형 센싱 기술

경력

• 2020년 9월 - 현재, 인공지능연구소 기술 리더 & 공동 창업자 @ SI Analytics
• 2017년 7월 - 2020년 2월, 머신러닝 및 컴퓨터 비전 연구원 @ Satrec Initiative

학위

• 2023년 2월 - 현재, KAIST, 대전, 대한민국
  • 문화기술대학원 석사 과정
• 2014년 3월 - 2021년 2월, GIST, 광주, 대한민국
  • 학사, 전기전자 및 컴퓨터 공학 전공

출판 이력 (Google Scholar)

• Self-Pair: Synthesizing Changes from Single Source for Object Change Detection in Remote Sensing Imagery
  • 
  • Minseok Seo, Hakjin Lee, Yongjin Jeon, and Junghoon Seo
  • IEEE WACV. 2023. Link
• Geometric Remove-and-Retrain (GOAR): Coordinate-Invariant eXplainable AI Assessment
  • 
  • Yonghyun Park, Junghoon Seo, Bomseok Park, Seongsu Lee, and Junghyo Jo
  • NeurIPS Workshop. 2023.
• Prototype-oriented Unsupervised Change Detection for Disaster Management
  • 
  • Youngtack Oh, Minseok Seo, Kim Doyi, and Junghoon Seo
  • NeurIPS Workshop. 2023. Link
• Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness
  • 
  • Beomsu Kim and Junghoon Seo
  • AISTATS. 2022. Link
• Quantile Autoencoder with Abnormality Accumulation for Anomaly Detection of Multi-variate Sensor Data
  • 
  • Seunghyoung Ryu, Jiyeon Yim, Junghoon Seo, Yonggyun Yu, and Hogeon Seo
  • IEEE Access. 2022. Link
• Contrastive Multiview Coding With Electro-Optics for SAR Semantic Segmentation
  • 
  • Keumgang Cha, Junghoon Seo, and Yeji Choi
  • IEEE GRSL. 2021. Link
• Training Domain-invariant Object Detector Faster with Feature Replay and Slow Learner
  • 
  • Chaehyeon Lee, Junghoon Seo, and Heechul Jung
  • CVPR Workshop. 2021. Link
• On the Power of Deep but Naive Partial Label Learning
  • 
  • Junghoon Seo and Joon Suk Huh
  • IEEE ICASSP. 2021. Link
• NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations
  • 
  • Yooseung Wang, Junghoon Seo, and Taegyun Jeon
  • IEEE GRSL. 2021. Link
• Revisiting Classical Bagging with Modern Transfer Learning for On-the-fly Disaster Damage Detector
  • 
  • Junghoon Seo, Seungwon Lee, Beomsu Kim, and Taegyun Jeon
  • NeurIPS Workshop. 2019. Link
• Deep Closed-Form Subspace Clustering
  • 
  • Junghoon Seo, Jamyoung Koo, and Taegyun Jeon
  • ICCV Workshop. 2019. Link
• Why are Saliency Maps Noisy? Cause of and Solution to Noisy Saliency Maps
  • 
  • Beomsu Kim, Junghoon Seo, Jeongyeol Choe, Jamyoung Koo, Seunghyeon Jeon, and Taegyun Jeon
  • ICCV Workshop. 2019. Link
• Bridging Adversarial Robustness and Gradient Interpretability
  • 
  • Beomsu Kim, Junghoon Seo, and Taegyun Jeon
  • ICLR Workshop. 2019. Link
• RBox-CNN: Rotated Bounding Box based CNN for Ship Detection in Remote Sensing Image
  • 
  • Jamyoung Koo, Junghoon Seo, Seunghyun Jeon, Jeongyeol Choe, and Taegyun Jeon
  • ACM SIGSPATIAL. 2018. Link
• Noise-adding Methods of Saliency Map as Series of Higher Order Partial Derivative
  • 
  • Junghoon Seo, Jeongyeol Choe, Jamyoung Koo, SeungHyun Jeon, Beomsu Kim, and Taegyun Jeon
  • ICML Workshop. 2018. Link
• Domain Adaptive Generation of Aircraft on Satellite Imagery via Simulated and Unsupervised Learning
  • 
  • Junghoon Seo, Seunghyun Jeon, and Taegyun Jeon
  • ACML Workshop. 2017. Link
• Multi-task Learning for Fine-grained Visual Classification of Aircraft
  • 
  • Seunghyun Jeon, Junghoon Seo and Taegyun Jeon
  • ACML Workshop. 2017.

수상 경력

• 2021년, GIST에서 최우수학부논문상으로 학부 졸업
• 2020년, xView2 Challange 5위
• 2018년, CVPR NTIRE Super-resolution Challange 4-5위
• 2018년, DOTA Challange 2위
• 2016년, KISTI National Supercomputing Competition 최우수상
• 2016년, the Qualcomm-GIST Innovation Award 수상

강연 및 발표

• Query as Representation: A Paradigm Shift in Computer Vision Caused by DETR @ Online. Nov 2022. YouTube (Korean)
• Recent XAI Trends in Deep Learning Era: (Under-)specification and Approaches @ KAERI. Feb 2020.
• Back to the Representation Learning with focusing on Visual Self-supervision @ ETRI. Jul 2019. Presentation (Korean)
• Deep Perceptual Super-resolution: Going Beyond Distortion @ KARI. Jul 2018. Presentation

리뷰어 활동

• IEEE Transactions on Pattern Analysis and Machine Intelligence
• IEEE Transactions on Neural Networks and Learning Systems
• IEEE Geoscience and Remote Sensing Letters
• Several Conferences including CVPR, AISTATS, BMVC…
• Several Workshops on ICCV, ICLR, CVPR…

특허

• Method for detecting object, granted, 10-2364882
• Method for detecting on-the-fly disaster damage based on image, granted, 10-2255998
• Method for predicting frame using deep learning, application, 10-2023-0115699
• Method, system, and computing device for generating an alternative image of a satellite or aerial image in which an image of an area of interest is replaced, application, 10-2023-0075347
• Method of training object prediction models using ambiguous labels, application, 10-2022-0000169
• Method for detecting object, application, 10-2021-0168545
• Method to detect object, application, 10-2021-0135451
• Method to detect object, application, 10-2021-0135451
• Method for data clustering, application, 10-2020-0107206