MLSP-P76.7
A BIMODAL APPROACH FOR DETECTING FATIGUE USING SPEECH AND PERSONAL ASSESSMENTS IN COLLEGE STUDENTS
Kapotaksha Das, Mihai Burzo, University of Michigan, United States of America; John Elson, Clay Maranville, Ford Motor Company, United States of America; Mohamed Abouelenien, University of Michigan, United States of America
Session:
MLSP-P76: Supervised and Semi-Supervised Learning Methods III Poster
Track:
Machine Learning for Signal Processing [ML]
Location:
Poster Area 9
Presentation Time:
Fri, 8 May, 09:00 - 11:00
Presentation
Discussion
Resources
No resources available.
Session MLSP-P76
MLSP-P76.1: SEMANTIC AND TEMPORAL-AWARE DISTILLATION FOR CLASS-INCREMENTAL LEARNING
Dongyan Guo, xusheng wang, Yuanhao zheng, xiaoyan wang, ying cui, Zhejiang University of Technology, China
MLSP-P76.2: LESS: LARGE LANGUAGE MODEL ENHANCED SEMI-SUPERVISED LEARNING FOR SPEECH FOUNDATIONAL MODELS USING IN-THE-WILD DATA
Wen Ding, Fan Qian, NVIDIA, China
MLSP-P76.3: RFGAT: GENERATIVE ADVERSARIAL TEACHER FOR CROSS-DOMAIN RFID ACTIVITY RECOGNITION
Hengbo Wang, Lvqing Yang, Yishu Qiu, School of Informatics Xiamen University, Xiamen, China, China; Zhipeng Liu, Zijin Zhixin Zhikong (Xiamen) Technology Co., Ltd, Xiamen, China, China; Kai Li, Xiamen University Research Institute of Artificial Intelligence, Xiamen, China, China; Bo Yu, Shihui Guo, School of Informatics Xiamen University, Xiamen, China, China
MLSP-P76.4: POSITIVE–AND–MULTI-NEGATIVE LEARNING WITH ADAPTIVE REWEIGHTING FOR NOISY LABELS
Chen-Chen Zong, Yu-Qi Chi, Tong Jin, Sheng-Jun Huang, Nanjing University of Aeronautics and Astronautics, China
MLSP-P76.5: WHEN THREE HEADS COLLABORATE: ATTENTION-DRIVEN FUSION FOR LONG-TAILED SEMI-SUPERVISED LEARNING
Ziyao Meng, Xue Gu, Adriano Tavares, Sandro Pinto, uminho, Portugal; Hao Xu, Jilin university, China
MLSP-P76.6: ATO: ADAPTIVE TARGET OPTIMIZATION FOR SEMI-SUPERVISED DOMAIN ADAPTATION VIA DEEP REINFORCEMENT LEARNING
GuSang Lee, Wooje Park, Donghoon Kim, Seoul National University, Korea, Republic of; Kyuhong Shim, Sungkyunkwan University, Korea, Republic of; Byonghyo Shim, Seoul National University, Korea, Republic of
MLSP-P76.7: A BIMODAL APPROACH FOR DETECTING FATIGUE USING SPEECH AND PERSONAL ASSESSMENTS IN COLLEGE STUDENTS
Kapotaksha Das, Mihai Burzo, University of Michigan, United States of America; John Elson, Clay Maranville, Ford Motor Company, United States of America; Mohamed Abouelenien, University of Michigan, United States of America
MLSP-P76.8: PAMNet: Patch-Adaptive Mixing Network for Multivariate Time Series Forecasting
Jiyanglin Li, Guizhou University of Finance and Economics, China; Wenjun Yu, Shanghai University of International Business and Economics, China; Heming Du, The University of Queensland, Australia; Yiming Tang, Shanghai Lixin University of Accounting and Finance, China; Jinhong You, Shanghai University of Finance and Economics, China; Shouguo Du, Shanghai Municipal Big Data Center, China; Wen Li, Shanghai University of International Business and Economics, China
MLSP-P76.9: DAM: Dual Active Learning with Multimodal Foundation Model for Source-Free Domain Adaptation
Xi Chen, Hongxun Yao, Zhaopan Xu, Kui Jiang, Harbin Institute of Technology, China
MLSP-P76.10: LEARNING FROM LABEL PROPORTIONS WITH SHRINKING BAG
Xueyou Lu, Jilin University, China; Yueyi Wang, Northeast Normal University, China; Wenxu Gao, Shenzhen Graduate School, Peking University, China
Contacts