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60,763 results on '"Pedrycz, Witold"'

103. Robust and Precise Facial Landmark Detection by Self-Calibrated Pose Attention Network

Author

Wan, Jun, Xi, Hui, Zhou, Jie, Lai, Zhihui, Pedrycz, Witold, Wang, Xu, and Sun, Hang

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Current fully-supervised facial landmark detection methods have progressed rapidly and achieved remarkable performance. However, they still suffer when coping with faces under large poses and heavy occlusions for inaccurate facial shape constraints and insufficient labeled training samples. In this paper, we propose a semi-supervised framework, i.e., a Self-Calibrated Pose Attention Network (SCPAN) to achieve more robust and precise facial landmark detection in challenging scenarios. To be specific, a Boundary-Aware Landmark Intensity (BALI) field is proposed to model more effective facial shape constraints by fusing boundary and landmark intensity field information. Moreover, a Self-Calibrated Pose Attention (SCPA) model is designed to provide a self-learned objective function that enforces intermediate supervision without label information by introducing a self-calibrated mechanism and a pose attention mask. We show that by integrating the BALI fields and SCPA model into a novel self-calibrated pose attention network, more facial prior knowledge can be learned and the detection accuracy and robustness of our method for faces with large poses and heavy occlusions have been improved. The experimental results obtained for challenging benchmark datasets demonstrate that our approach outperforms state-of-the-art methods in the literature., Comment: Accept by IEEE Transactions on Cybernetics, December 2021

Published
2021

118. An Overview and Experimental Study of Learning-based Optimization Algorithms for Vehicle Routing Problem

Author

Li, Bingjie, Wu, Guohua, He, Yongming, Fan, Mingfeng, and Pedrycz, Witold

Subjects
Computer Science - Machine Learning
Abstract

Vehicle routing problem (VRP) is a typical discrete combinatorial optimization problem, and many models and algorithms have been proposed to solve the VRP and its variants. Although existing approaches have contributed a lot to the development of this field, these approaches either are limited in problem size or need manual intervening in choosing parameters. To solve these difficulties, many studies have considered the learning-based optimization (LBO) algorithms to solve the VRP. This paper reviews recent advances in this field and divides relevant approaches into end-to-end approaches and step-by-step approaches. We performed a statistical analysis of the reviewed articles from various aspects and designed three experiments to evaluate the performance of four representative LBO algorithms. Finally, we conclude the applicable types of problems for different LBO algorithms and suggest directions in which researchers can improve LBO algorithms., Comment: 23 pages, 11 figures

Published
2021

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