Feng Zhou
Feng Zhou
Assistant Professor at University of Michigan, Dearborn
Verified email at - Homepage
Cited by
Cited by
Trends in augmented reality tracking, interaction and display: A review of ten years of ISMAR
F Zhou, HBL Duh, M Billinghurst
2008 7th IEEE/ACM International Symposium on Mixed and Augmented Reality …, 2008
Melanoma recognition in dermoscopy images via aggregated deep convolutional features
Z Yu, X Jiang, F Zhou, J Qin, D Ni, S Chen, B Lei, T Wang
IEEE Transactions on Biomedical Engineering 66 (4), 1006-1016, 2018
Compact generalized non-local network
K Yue, M Sun, Y Yuan, F Zhou, E Ding, F Xu
Advances in neural information processing systems 31, 2018
Deep learning framework for Alzheimer’s disease diagnosis via 3D-CNN and FSBi-LSTM
C Feng, A Elazab, P Yang, T Wang, F Zhou, H Hu, X Xiao, B Lei
IEEE Access 7, 63605-63618, 2019
Affective and cognitive design for mass personalization: status and prospect
F Zhou, Y Ji, RJ Jiao
Journal of Intelligent Manufacturing 24 (5), 1047-1069, 2013
A robust audio watermarking scheme based on lifting wavelet transform and singular value decomposition
B Lei, Y Soon, F Zhou, Z Li, H Lei
Signal processing 92 (9), 1985-2001, 2012
A case-driven ambient intelligence system for elderly in-home assistance applications
F Zhou, JR Jiao, S Chen, D Zhang
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2010
Dense deconvolutional network for skin lesion segmentation
H Li, X He, F Zhou, Z Yu, D Ni, S Chen, T Wang, B Lei
IEEE journal of biomedical and health informatics 23 (2), 527-537, 2018
Latent Customer Needs Elicitation by Use Case Analogical Reasoning From Sentiment Analysis of Online Product Reviews
F Zhou, R Jiao, JS Linsey
ASME Journal of Mechanical Design 137 (7), 071401 (Jul 01, 2015) (12 pages), 2015
A deeply supervised residual network for HEp-2 cell classification via cross-modal transfer learning
H Lei, T Han, F Zhou, Z Yu, J Qin, A Elazab, B Lei
Pattern Recognition 79, 290-302, 2018
Examining the Effects of Emotional Valence and Arousal on Takeover Performance in Conditionally Automated Driving
N Du, F Zhou, E Pulver, DM Tilbury, LP Robert, AK Pradhan, XJ Yang
Transportation Research Part C: Emerging Technologies, 2020
Combat COVID-19 Infodemic Using Explainable Natural Language Processing Models  
J Ayoub, XJ Yang, F Zhou
Information Processing and Management, 2021
From Manual Driving to Automated Driving: A Review of 10 Years of AutoUI
J Ayoub, F Zhou, S Bao, XJ Yang
11th International ACM Conference on Automotive User Interfaces and …, 2019
Affect prediction from physiological measures via visual stimuli
F Zhou, X Qu, MG Helander, JR Jiao
International Journal of Human-Computer Studies 69 (12), 801-819, 2011
Predicting Driver Takeover Performance in Conditionally Automated Driving
N Du, F Zhou, E Pulver, D Tilbury, L Robert, A Pradhan, XJ Yang
Accident Analysis & Prevention, 2020
Driver fatigue transition prediction in highly automated driving using physiological features
F Zhou, A Alsaid, M Blommer, R Curry, R Swaminathan, D Kochhar, ...
Expert Systems with Applications 147, 113204, 2020
Emotion Prediction from Physiological Signals: A Comparison Study Between Visual and Auditory Elicitors
F Zhou, X Qu, JR Jiao, MG Helander
Interacting with Computers 26 (3), 285-302, 2014
Psychophysiological responses to takeover requests in conditionally automated driving
N Du, XJ Yang, F Zhou
Accident Analysis & Prevention, 2020
Using Eye-tracking Data to Predict Situation Awareness in Real Time during Takeover Transitions in Conditionally Automated Driving
F Zhou, XJ Yang, J de Winter
IEEE Transactions on Intelligent Transportation Systems, 2021
Deep and joint learning of longitudinal data for Alzheimer's disease prediction
B Lei, M Yang, P Yang, F Zhou, W Hou, W Zou, X Li, T Wang, X Xiao, ...
Pattern Recognition 102, 107247, 2020
The system can't perform the operation now. Try again later.
Articles 1–20