Machine Learning Techniques for Consumer Electronics Applications
Submission Guideline:
The submission guideline could be found on https://icce.org/2023/Submission-Guidelines.html
Submission site in EDAS: https://edas.info/N29720
Description:
The workshop on machine learning techniques for consumer electronics applications intends to provide a forum for researchers, educators, and professionals to exchange their discoveries and practices, and to explore future trends and applications in consumer electronics and artificial intelligence. Your Participation at the workshop would be an excellent opportunity for you to meet other researchers and to discuss the technology advancements. The workshop of the 41-th IEEE International Conference on Consumer Electronics (ICCE 2023) will be held on January 06, 2023.
Topics:
Areas of interest include, but are not limited to, the following topics:
· Decision Tree for Consumer Electronics Applications
· Random Forest for Consumer Electronics Applications
· K-Nearest Neighbor for Consumer Electronics Applications
· Bayes Classification for Consumer Electronics Applications
· Support Vector Machine for Consumer Electronics Applications
· Neural Network for Consumer Electronics Applications
· Convolutional Neural Network for Consumer Electronics Applications
· Recurrent Neural Network for Consumer Electronics Applications
· Long Short-Term Memory for Consumer Electronics Applications
· Restricted Boltzmann Machine for Consumer Electronics Applications
· Deep Boltzmann Machine for Consumer Electronics Applications
· Association Rules for Consumer Electronics Applications
· Clustering Techniques for Consumer Electronics Applications
· Generative Adversarial Network for Consumer Electronics Applications
· Reinforcement Learning Techniques for Consumer Electronics Applications
· Federated Learning Techniques for Consumer Electronics Applications
· Machine Learning Techniques for Consumer Electronics Applications
· Machine Learning Techniques for Applications
Organizing Committee:
General Chairs:
· Prof. Cheng Shi (Xi'an University of Technology, China)
· Prof. Yu-Chih Wei (National Taipei University of Technology, Taiwan)
· Prof. Chia-Yu Lin (National Central University, Taiwan)
· Prof. Genggeng Liu (Fuzhou University, China)
Session Chairs:
· Prof. Hsiao-Ting Tseng (National Central University, Taiwan)
· Prof. Feng-Jang Hwang (National Sun Yat-sen University, Taiwan)
· Dr. Chi-Hua Chen (Fuzhou University, China)
TPC members:
· Prof. Ting Bi (Maynooth University, Ireland)
· Prof. Jiayuan Xin (Newcastle University, UK)
· Dr. Lingjuan Lyu (Sony AI Inc., Japan)
· Prof. Hsu-Yang Kung (National Pingtung University of Science and Technology, Taiwan)
· Prof. Hao-Chun Lu (National Yang Ming Chiao Tung University, Taiwan)
· Prof. Yao-Huei Huang (Fu-Jen Catholic University, Taiwan)
· Prof. Fangyin Song (Fuzhou University, China)
· Prof. Ling Wu (Fuzhou University, China)
· Prof. Xiaoyan Li (Fuzhou University, China)
· Prof. Lei Xiong (Guangzhou Academy of Fine Arts, China)
· Prof. Bo-Wei Zhu (Macau University of Science and Technology, Macau)