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안녕하십니까? KAIST 설명가능인공지능 연구센터는 과학기술정보통신부의 후원으로 설립된 연구센터로, 지난 2020년 1월 한국과학기술원에 새 터전을 마련하고 고려대학교, 서울대학교, 연세대학교, UNIST와 AITRICS 소속 250여명의 연구원들이 세계적 수준의 연구를 진행하고 있으며, 미국 DARPA, 독일 베를린 빅데이터 센터등 해외 기관과도 활발하게 교류하고 있습니다. 본… Continue Reading →
KAIST AI대학원 성남연구센터 제1회 기술설명회가 2020년 10월 16일 금요일 13:00~18:00에 개최됩니다. 본 설명회는 Zoom을 이용해 온라인으로 개최됩니다. 사전신청을 통해 참가신청을 받고 있으며, 신청자에 한하여 개별상담도 진행됩니다. 포스터의 QR코드 또는 아래의 링크를 통해 사전신청이 가능합니다. – 사전 신청 링크: http://gg.gg/KAISTGSAI
[IEEE ISBI 2016 Challenge] Ranked 1st and 3rd in Skin Cancer Classification Challenges (April 2016).
Congrats that our members Thanh, Haebeom and Janghoon ranked 1st and 3rd in ISBI 2016: Skin Lesion Analysis Towards Melanoma Detection Challenges! https://challenge.kitware.com/#challenge/560d7856cad3a57cfde481ba Thanh and Janghoon’s submission ranked first in identifying dermoscopic features. https://challenge.kitware.com/#phase/56fc26f7cad3a54f8bb80e4c Haebeom and Janghoon’s submission ranked 3rd… Continue Reading →
We have posted our results on PASCAL VOC Semantic Segmentation Results (VOC2012). As a (unique research team count), our team (model name: UNIST_GDN) performs 71.8%* (Average Precision %) and is in the 8th position after Oxford, Adelaid, The Chinese University of Hong… Continue Reading →
Prof. Choi is invited for talks in national conferences and a university colloquium. – Machine Learning Based Plant Diagnosis, Symposium on big data application of chemical and energy processes, 2015 Fall Symposium of the Korean Institute of Chemical Engineering, October… Continue Reading →
A new pragmatic archiving scheme for spatio-temporal sensor data! Paper, A Scalable and Flexible Repository for Big Sensor Data by Dongeun Lee, Prof. Heonshik Shin (Seoul National University) and Jaesik Choi is accepted at IEEE Sensors Journal.
We are excited that 6 new talented researchers/grad students join our lab in this fall. Dr Kallol Roy (BS from IIT Kanpur, PhD from Indian Institute of Science (IISC), India) joins as a postdoc in mid August, 2015. Vladimir Nekrasov (BS… Continue Reading →
A new way of predicting changes of stock market by reading news articles! Paper, Reading Documents for Bayesian Online Change Point Detection by Taehoon Kim (undergrad) and Jaesik Choi is accepted at 2015 Empirical Methods in Natural Language Processing (EMNLP-15).
A report on machine learning of Prof. Choi is published in the expert report series for Legislative Knowledge Service (NEXT) of National Assembly Library of Korea.
We are exited that eight undergraduate interns join our lab in this summer. Three students (Azamatbek Akhmedov, Sol-A Kim and Wonjun Yoon) join from UNIST. Through the U-SURF program, Jungwoon Shin (Boston Univ., USA), Guhnoo Yun (Kyungsang Univ.) and Sorang Cho… Continue Reading →
