Search Results - "semi-supervised convolutional variational autoencoder"

Fault diagnosis for high-dimensional complex processes using semi-supervised deep convolutional generative models ; 준지도학습 심층 생성 모델을 활용한 공정 고장 분류

Authors: Ko, Taeyoung Kim, Heeyoung 김희영 et al.

Contributors: Ko, Taeyoung Kim, Heeyoung 김희영 et al.

Subject Terms: convolutional auxiliary deep generative model▼amultivariate time series, semi-supervised convolutional variational autoencoder▼aTennessee Eastman process▼aunlabeled data, 합성곱 보조변수 심층 생성 모델▼a다변수 시계열▼a준지도학습 합성곱 변분 오토인코더▼a테네시 이스트만 공정▼a레이블이 없는 데이터

Relation: 843192; http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=843192&flag=dissertation; http://hdl.handle.net/10203/266236; 325007; 1935

Availability: http://hdl.handle.net/10203/266236
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=843192&flag=dissertation

Deep Residual Learning-Based Convolutional Variational Autoencoder For Driver Fatigue Classification

Authors: Sameera Adhikari Senaka Amarakeerthi

Source: Advances in Technology. :277-290

Subject Terms: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Fault Classification in High-Dimensional Complex Processes Using Semi-Supervised Deep Convolutional Generative Models.

Authors: Ko, Taeyoung Kim, Heeyoung

Source: IEEE Transactions on Industrial Informatics; Apr2020, Vol. 16 Issue 4, p2868-2877, 10p