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IEEE Transactions on Cybernetics Publication Information
Year: 2022 | Volume: 52 | Issue: 12
Interpretability-Based Multimodal Convolutional Neural Networks for Skin Lesion Diagnosis
Sutong Wang;Yunqiang Yin;Dujuan Wang;Yanzhang Wang;Yaochu Jin
Publication Year: 2022,Page(s):12623 - 12637
Cited by: Papers (40)
Skin lesion diagnosis is a key step for skin cancer screening, which requires high accuracy and interpretability. Though many computer-aided methods, especially deep learning methods, have made remarkable achievements in skin lesion diagnosis, their generalization and interpretability are still a challenge. To solve this issue, we propose an interpretability-based multimodal convolutional neural n...Show More
Observer-Based Asynchronous Control of Nonlinear Systems With Dynamic Event-Based Try-Once-Discard Protocol
Publication Year: 2022,Page(s):12638 - 12648
Cited by: Papers (55)
This work investigates the observer-based asynchronous control of discrete-time nonlinear systems with network-induced communication constraints. To avoid the data collisions and side effects in a constrained communication channel, a novel dynamic event-based weighted try-once-discard (DEWTOD) protocol is proposed. In contrast to the existing protocols, the DEWTOD scheduling regulates whether the ...Show More
Point Adversarial Self-Mining: A Simple Method for Facial Expression Recognition
Ping Liu;Yuewei Lin;Zibo Meng;Lu Lu;Weihong Deng;Joey Tianyi Zhou;Yi Yang
Publication Year: 2022,Page(s):12649 - 12660
Cited by: Papers (28)
In this article, we propose a simple yet effective approach, called point adversarial self mining (PASM), to improve the recognition accuracy in facial expression recognition (FER). Unlike previous works focusing on designing specific architectures or loss functions to solve this problem, PASM boosts the network capability by simulating human learning processes: providing updated learning material...Show More
WaSR—A Water Segmentation and Refinement Maritime Obstacle Detection Network
Publication Year: 2022,Page(s):12661 - 12674
Cited by: Papers (48)
Obstacle detection using semantic segmentation has become an established approach in autonomous vehicles. However, existing segmentation methods, primarily developed for ground vehicles, are inadequate in an aquatic environment as they produce many false positive (FP) detections in the presence of water reflections and wakes. We propose a novel deep encoder–decoder architecture, a water segmentati...Show More
WaSR—A Water Segmentation and Refinement Maritime Obstacle Detection Network
Year: 2022 | Volume: 52 | Issue: 12
A Self-Learning Discrete Jaya Algorithm for Multiobjective Energy-Efficient Distributed No-Idle Flow-Shop Scheduling Problem in Heterogeneous Factory System
Publication Year: 2022,Page(s):12675 - 12686
Cited by: Papers (134)
In this study, a self-learning discrete Jaya algorithm (SD-Jaya) is proposed to address the energy-efficient distributed no-idle flow-shop scheduling problem (FSP) in a heterogeneous factory system (HFS-EEDNIFSP) with the criteria of minimizing the total tardiness (TTD), total energy consumption (TEC), and factory load balancing (FLB). First, the mixed-integer programming model of HFS-EEDNIFSP is ...Show More
An Integrated Model-Based and Data-Driven Gap Metric Method for Fault Detection and Isolation
Publication Year: 2022,Page(s):12687 - 12697
Cited by: Papers (28)
This article proposes an integrated approach of model-based and data-driven gap metric fault detection and isolation in a stochastic framework. For actuator and sensor faults, an adaptive Kalman filter combining with the generalized likelihood ratio method is suggested. For component faults, especially incipient faults, the model-based scheme maybe not a good choice due to the existence of disturb...Show More
Learning to Optimize: Reference Vector Reinforcement Learning Adaption to Constrained Many-Objective Optimization of Industrial Copper Burdening System
Lianbo Ma;Nan Li;Yinan Guo;Xingwei Wang;Shengxiang Yang;Min Huang;Hao Zhang
Publication Year: 2022,Page(s):12698 - 12711
Cited by: Papers (106)
The performance of decomposition-based algorithms is sensitive to the Pareto front shapes since their reference vectors preset in advance are not always adaptable to various problem characteristics with no a priori knowledge. For this issue, this article proposes an adaptive reference vector reinforcement learning (RVRL) approach to decomposition-based algorithms for industrial copper burdening op...Show More
Robust Composite H∞ Synchronization of Markov Jump Reaction–Diffusion Neural Networks via a Disturbance Observer-Based Method
Publication Year: 2022,Page(s):12712 - 12721
Cited by: Papers (10)
This article focuses on the composite $\mathcal {H}_{\infty }$ synchronization problem for jumping reaction–diffusion neural networks (NNs) with multiple kinds of disturbances. Due to the existence of disturbance effects, the performance of the aforementioned system would be degraded; therefore, improving the control performance of closed-loop NNs is the main goal of this article. Notably, for t...Show More
Consensus-Based Labeled Multi-Bernoulli Filter for Multitarget Tracking in Distributed Sensor Network
Publication Year: 2022,Page(s):12722 - 12733
Cited by: Papers (28)
This article introduces a novel consensus-based labeled multi-Bernoulli (LMB) filter to tackle multitarget tracking (MTT) in a distributed sensor network (DSN), whose sensor nodes have limited and different fields of view (FoVs). Although consensus-based algorithms are effective for distributed fusion and MTT, it may be problematic when distributed sensor nodes have different FoVs. To deal with th...Show More
Self-Guided Deep Multiview Subspace Clustering via Consensus Affinity Regularization
Publication Year: 2022,Page(s):12734 - 12744
Cited by: Papers (14)
Multiview subspace clustering (MVSC) leverages the complementary information among different views of multiview data and seeks a consensus subspace clustering result better than that using any individual view. Though proved effective in some cases, existing MVSC methods often obtain unsatisfactory results since they perform subspace analysis with raw features that are often of high dimensions and ...Show More
Multiview Learning With Robust Double-Sided Twin SVM
Qiaolin Ye;Peng Huang;Zhao Zhang;Yuhui Zheng;Liyong Fu;Wankou Yang
Publication Year: 2022,Page(s):12745 - 12758
Cited by: Papers (127)
Multiview learning (MVL), which enhances the learners’ performance by coordinating complementarity and consistency among different views, has attracted much attention. The multiview generalized eigenvalue proximal support vector machine (MvGSVM) is a recently proposed effective binary classification method, which introduces the concept of MVL into the classical generalized eigenvalue proximal supp...Show More
Multiview Learning With Robust Double-Sided Twin SVM
Qiaolin Ye;Peng Huang;Zhao Zhang;Yuhui Zheng;Liyong Fu;Wankou Yang
Year: 2022 | Volume: 52 | Issue: 12
Compensation-Based Output Feedback Control for Fuzzy Markov Jump Systems With Random Packet Losses
Publication Year: 2022,Page(s):12759 - 12770
Cited by: Papers (27)
This article is concerned with the problem of compensation-based output feedback control for Takagi–Sugeno fuzzy Markov jump systems subject to packet losses. The phenomenon of packet losses is assumed to randomly occur in the feedback channel, which is modeled by a Bernoulli process. Employing the single exponential smoothing method as a compensation scheme, the missing measurements are predicted...Show More
Smoothness Sensor: Adaptive Smoothness-Transition Graph Convolutions for Attributed Graph Clustering
Publication Year: 2022,Page(s):12771 - 12784
Cited by: Papers (7)
Clustering techniques attempt to group objects with similar properties into a cluster. Clustering the nodes of an attributed graph, in which each node is associated with a set of feature attributes, has attracted significant attention. Graph convolutional networks (GCNs) represent an effective approach for integrating the two complementary factors of node attributes and structural information for ...Show More
Decentralized Robust Portfolio Optimization Based on Cooperative-Competitive Multiagent Systems
Publication Year: 2022,Page(s):12785 - 12794
Cited by: Papers (22)
This article addresses decentralized robust portfolio optimization based on multiagent systems. Decentralized robust portfolio optimization is first formulated as two distributed minimax optimization problems in a Markowitz return-risk framework. Cooperative-competitive multiagent systems are developed and applied for solving the formulated problems. The multiagent systems are shown to be able to ...Show More
Adaptive Fuzzy Output-Feedback Decentralized Control for Fractional-Order Nonlinear Large-Scale Systems
Publication Year: 2022,Page(s):12795 - 12804
Cited by: Papers (33)
This article studies the adaptive fuzzy output-feedback decentralized control problem for the fractional-order nonlinear large-scale systems. Since the considered strict-feedback systems contain unknown nonlinear functions and unmeasurable states, the fuzzy-logic systems (FLSs) are used to model unknown fractional-order subsystems, and a fuzzy decentralized state observer is established to obtain ...Show More
Attacks on Formation Control for Multiagent Systems
Publication Year: 2022,Page(s):12805 - 12817
Cited by: Papers (74)
Multiagent systems (MASs) are distributed systems with two or more intelligent agents. Formation control is a significant control technique of MASs. To date, formation control on MASs is widely used in various fields, such as robots, spacecrafts, satellites, and unmanned aerial/surface/underwater vehicles. However, there is a relatively small body of literature that is concerned with security prob...Show More
Roto-Translation Invariant Formation of Multiple Underactuated Planar Rigid Bodies
Publication Year: 2022,Page(s):12818 - 12831
Cited by: Papers (4)
This article investigates the roto-translation invariant (RTI) formation of multiple underactuated planar rigid bodies, which are established under the framework of matrix Lie groups. The main contribution is that we define the RTI and pseudo RTI (P-RTI) formation of planar rigid bodies. Different from the common formation given in the earth-fixed frame, the RTI formation is defined in the body-fi...Show More
Optimal Consensus Control Design for Multiagent Systems With Multiple Time Delay Using Adaptive Dynamic Programming
Publication Year: 2022,Page(s):12832 - 12842
Cited by: Papers (63)
In this article, a novel data-based adaptive dynamic programming (ADP) method is presented to solve the optimal consensus tracking control problem for discrete-time (DT) multiagent systems (MASs) with multiple time delays. Necessary and sufficient conditions of the corresponding equivalent time-delay system are provided on the basis of the causal transformations. Benefitting from the construction ...Show More
Adaptive Neural-Network-Based Fault-Tolerant Control for a Flexible String With Composite Disturbance Observer and Input Constraints
Publication Year: 2022,Page(s):12843 - 12853
Cited by: Papers (78)
We propose an adaptive neural-network-based fault-tolerant control scheme for a flexible string considering the input constraint, actuator gain fault, and external disturbances. First, we utilize a radial basis function neural network to compensate for the actuator gain fault. In addition, an observer is used to handle composite disturbances, including unknown approximation errors and boundary dis...Show More
Evolutionary Multitasking Multilayer Network Reconstruction
Publication Year: 2022,Page(s):12854 - 12868
Cited by: Papers (28)
Due to the multilayer nature of real-world systems, the problem of inferring multilayer network structures from nonlinear and complex dynamical systems is prominent in many fields, including engineering, biological, physical, and computer sciences. Many network reconstruction methods have been proposed to address this problem, but none of them consider the similarities among network reconstruction...Show More
A Novel Method for Constructing EEG Large-Scale Cortical Dynamical Functional Network Connectivity (dFNC): WTCS
Chanlin Yi;Ruwei Yao;Liuyi Song;Lin Jiang;Yajing Si;Peiyang Li;Fali Li;Dezhong Yao;Yu Zhang;Peng Xu
Publication Year: 2022,Page(s):12869 - 12881
Cited by: Papers (25)
As a kind of biological network, the brain network conduces to understanding the mystery of high-efficiency information processing in the brain, which will provide instructions to develop efficient brain-like neural networks. Large-scale dynamical functional network connectivity (dFNC) provides a more context-sensitive, dynamical, and straightforward sight at a higher network level. Nevertheless, ...Show More
Variational Progressive-Transfer Network for Soft Sensing of Multirate Industrial Processes
Publication Year: 2022,Page(s):12882 - 12892
Cited by: Papers (34)
Deep-learning-based soft sensors have been extensively developed for predicting key quality or performance variables in industrial processes. However, most approaches assume that data are uniformly sampled while the multiple variables are often acquired at different rates in practical processes. This article designed a progressive transfer strategy, based on which a variational progressive-transfe...Show More
No Need for Landmarks: An Embodied Neural Controller for Robust Insect-Like Navigation Behaviors
Publication Year: 2022,Page(s):12893 - 12904
Cited by: Papers (6)
Bayesian filters have been considered to help refine and develop theoretical views on spatial cell functions for self-localization. However, extending a Bayesian filter to reproduce insect-like navigation behaviors (e.g., home searching) remains an open and challenging problem. To address this problem, we propose an embodied neural controller for self-localization, foraging, backward homing (BH), ...Show More
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