Results 201 to 210 of about 2,721,063 (244)

A Feature Space-Restricted Attention Attack on Medical Deep Learning Systems

IEEE Transactions on Cybernetics, 2022
Deep neural network has shown a powerful performance in the medical image analysis of a variety of diseases. However, a number of studies over the past few years have demonstrated that these deep learning systems can be vulnerable to well-designed ...
Zizhou Wang, Xin Shu, Yan Wang, Yangqin Feng, Lei Zhang, Zhang Yi   +5 more
semanticscholar   +1 more source

Recognition of variety: considering learning with digital games as cybernetic systems

International Journal of Technology Enhanced Learning, 2011
In this paper, the author proposes cybernetics as a valid scientific and theoretical approach in considering the requisite variety of learners and learning through the application of digital games. The paper challenges anecdotal notions of perceived generational distinctions in respect of their pre-disposition to using games in learning.
openaire   +2 more sources

A Community Structure Enhancement-Based Community Detection Algorithm for Complex Networks

IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021
Community detection has been recognized as one of the most important tools to discover useful information hidden in complex networks which is usually hard to be obtained by simple observations.
Yansen Su, Chunlong Liu, Yunyun Niu, Fan Cheng, Xing-yi Zhang   +4 more
semanticscholar   +1 more source

An Iterative Greedy Algorithm With Q-Learning Mechanism for the Multiobjective Distributed No-Idle Permutation Flowshop Scheduling

IEEE Transactions on Systems, Man, and Cybernetics: Systems
The distributed no-idle permutation flowshop scheduling problem (DNIPFSP) has widely existed in various manufacturing systems. The makespan and total tardiness are optimized simultaneously considering the variety of scales of the problems with ...
Fuqing Zhao, Changxue Zhuang, Ling Wang, Chenxin Dong   +3 more
semanticscholar   +1 more source

Trend-Based Granular Representation of Time Series and its Application in Clustering

IEEE Transactions on Cybernetics, 2021
Granular computing has been an intense research area over the past two decades, focusing on acquiring, processing, and interpreting information granules.
Hongyue Guo, Lidong Wang, Xiaodong Liu, W. Pedrycz   +3 more
semanticscholar   +1 more source

Bi-objective Elite Differential Evolution Algorithm for Multivalued Logic Networks

IEEE Transactions on Cybernetics, 2020
In this paper, a novel algorithm called bi-objective elite differential evolution (BOEDE) is proposed to optimize multivalued logic (MVL) networks. It is a multiobjective algorithm completely different from all previous single-objective optimization ones.
Jian Sun, Shangce Gao, Hongwei Dai, Jiujun Cheng, Mengchu Zhou, Jiahai Wang   +5 more
semanticscholar   +1 more source

Deep Reinforcement Learning Framework for Category-Based Item Recommendation

IEEE Transactions on Cybernetics, 2021
Deep reinforcement learning (DRL)-based recommender systems have recently come into the limelight due to their ability to optimize long-term user engagement.
Mingsheng Fu, Anubha Agrawal, Athirai Aravazhi Irissappane, J. Zhang, Liwei Huang, Hongjiao Qu   +5 more
semanticscholar   +1 more source

Multisensor integration and fusion in intelligent systems

IEEE Transactions on Systems, Man and Cybernetics, 1989
The issues involved in integrating multiple sensors into the operation of a system are presented in the context of the type of information these sensors can uniquely provide. A survey is provided of the variety of approaches to the problem of multisensor
R. Luo, M. Kay
semanticscholar   +1 more source

DLIN: Deep Ladder Imputation Network

IEEE Transactions on Cybernetics, 2021
Many efforts have been dedicated to addressing data loss in various domains. While task-specific solutions may eliminate the respective issue in certain applications, finding a generic method for missing data estimation is rather complex. In this regard,
Ehsan Hallaji, R. Razavi-Far, M. Saif
semanticscholar   +1 more source

Embedding Attention and Residual Network for Accurate Salient Object Detection

IEEE Transactions on Cybernetics, 2020
Salient object detection is usually used as a preprocessing step to facilitate a variety of subsequent applications which should take little time cost. With the quick development of deep learning recently, profound progresses have been made to achieve a ...
Shuhan Chen, Benge Wang, Xiuli Tan, Xuelong Hu   +3 more
semanticscholar   +1 more source