ICONIP 2011 학회 출장기 (Shanghai, China) Dept. of Computer Science, Yonsei University 이영설.

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ICONIP 2011 학회 출장기 (Shanghai, China) Dept. of Computer Science, Yonsei University 이영설

학회 장소 및 기간 장소 –Shanghai, China 기간 –11/14~11/16 1

주요 연구 Stable and Fast Decision by Neural Networks: Fundamental Problems in Mathematical Neuroscience –신경망 원리를 규명 신경망 앙상블, 시간에 따라 변화하는 피드백에 따른 신경망의 trace –Statistical neuro dynamics 소개 신경망의 state transition 표현 Garden of Eden 에서 시작해서 Attractor statues 에 도달 하나의 layer 를 통과할때마다 state transition 이 발생 Recent Advances in the Neocognitron: Robust Recognition of Visual Patterns –문자인식에 대한 신경망 구현이 인상적 –뇌의 특정 부분에 문자가 인식되는 과정 시각화 –Hidden layer 에서 변환 과정을 거쳐 최종적으로 하나의 점으로 수렴 Self-Learning Control of Nonlinear Systems based on Iterative Adaptive Dynamic Programming Approach –베이지안 음양 시스템 –음양의 원리에 부합하는 베이지안 네트워크의. statistical learning 2

주요 연구 A Classification Approach to the Cocktail Party Problem –여러 가지 소리가 섞여 있을 때 주요 음향만 골라서 인식 –예) 음성인식 : 복잡하게 얽힌 노이즈 속에서 원하는 음성 추출 –노이즈 제거가 가장 중요한 문제 –일반적인 해결 방법 (1) speech enhancement (2) spatial filtering –SVM 과 IBM(Ideal Binary Mask)을 이용한 방법 제시 Dynamic Bayesian Network Modeling of Cyanobacterial Biological Processes via Gene Clustering –Cyanobacteria : 광합성으로 에너지를 생산하는 박테리아 –베이지안 네트워크를 이용한 박테리아 유전자 특징 분석 데이터 필터링 K-Means 클러스터링 (Consensus Index : 다양성 측정에 이용) Dynamic Bayesian network 학습 (구글의 Global MIT 알고리즘 이용) 3

EEG 관련 연구 특징 –한 세션 전체가 EEG 관련 연구로 채워짐 –대부분의 연구가 32개 채널~16채널 사용 (60%가 32채널, 40%가 16채널) EEG-based brain-computer interface for dual task driving detection –운전 시뮬레이션 게임을 대상으로 이상 운전 (차선 침범등) 을 검출 –이상 운전이 발생했을 경우의 뇌파 변화를 체크 –SOM 을 이용하여 clustering (single driving & distracted driving) –Single driving 4 종류, 이상운전을 5 종류로 구분하여 모델링 4

EEG 관련 연구 EEG-based motion sickness estimation using principal component regression –사람들이 동작이 힘든 장애가 발생하는 경우를 가정 –10분 정상 – 40분 비정상 – 10분 정상 의 시나리오 사용 –PCA 와 clustering 을 이용하여 인식 (인식 정확도 : 약 78% 정도) Reading Your Mind: EEG During Reading Task –Reading relevant paragraphs / irrelevant paragraph 구분 –신경망을 사용하여 인식 (그러나 2 layer 만을 가진 신경망 사용) 5

느낀점 질문 1개 나온 내용 –SVM 과 학습된 standard BN 과 성능을 비교했는데, 제안한 방법은 어떻게 CPT를 세팅했는가? –답변 ) Activity hierarchy 랑 Context hierarchy 를 참조하여 BN 구조는 고정된 상태에 서 conditional probability 만 학습하였음. –뱅킷이 있는 날 오후 세션이라서 좌장이 빨리 끝내려고 함. 발표 전에 스크립트 외우는 게 중요 상해 날씨 생각보다 덥고 습함 –추울거라 예상하고 긴팔 옷만 준비하였음. EEG를 이용한 연구가 많아지고 있음 6