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AI，复杂网络，自然语言处理，深度学习，神经网络，多智能体系统，机器人，迭代控制...

全球科研机构

美国Florida Atlantic University；英国University of Portsmouth；新加坡Nanyang Technological University、Institute for Infocomm Research, Agency for Science, Technology and Research；西班牙University of Granada；日本University of Toyama；荷兰Eindhoven University of Technology；清华大学、中科院数学与系统科学研究院、北京航空航天大学、电子科技大学、中国科学技术大学、华中科技大学...

 

Y. Ming, N. N. Hu, C. X. Fan, F. Feng, J. W. Zhou, and  H. Yu,  “Visuals to text : A comprehensive review on automatic image captioning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1339–1365, Aug. 2022. doi: 10.1109/JAS.2022.105734

> Conducting a comprehensive review of image captioning, covering both traditional methods and recent deep learning-based techniques, as well as the publicly available datasets, evaluation metrics, the open issues and challenges.

> Focusing on the deep learning-based image captioning researches, which is categorized into the encoder-decoder framework, attention mechanism and training strategies on the basis of model structures and training manners for a detailed introduction.

> Discussing several future research directions of image captioning, such as Flexible Captioning, Unpaired Captioning, Paragraph Captioning and Non-Autoregressive Captioning.

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J. H. Lü, G. H. Wen, R. Q. Lu, Y. Wang, and  S. M. Zhang,  “Networked knowledge and complex networks: An engineering view,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1366–1383, Aug. 2022. doi: 10.1109/JAS.2022.105737

> State-of-the-art advances of complex networks and deep learning were briefly reviewed.

> A new framework of networked knowledge was suggested from the perspective of complex networks.

> Deep learning technologies for networked knowledge were reviewed and analyzed.

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S. W. Wang, X. Q. Zhu, W. P. Ding, and  A. A. Yengejeh,  “Cyberbullying and cyberviolence detection: A triangular user-activity-content view,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1384–1405, Aug. 2022. doi: 10.1109/JAS.2022.105740

> A comprehensive review of computational approaches for cyberbullying and cyberviolence detection.

> A UAC triangle view of the key factors in cyberbullying.

> Important features and their interactions in cyberbullying detection.

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C. Y. Lee, H. Hasegawa, and  S. C. Gao,  “Complex-valued neural networks: A comprehensive survey,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1406–1426, Aug. 2022. doi: 10.1109/JAS.2022.105743

> A comprehensive collection of variants of CVNNs are presented to provide their various structures.

> A systematic categorization of the recent applications of CVNNs provides an easy reference.

> Future research prospective on CVNNs are discussed.

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R. B. Jin, M. Wu, K. Y. Wu, K. Z. Gao, Z. H. Chen, and  X. L. Li,  “Position encoding based convolutional neural networks for machine remaining useful life prediction,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1427–1439, Aug. 2022. doi: 10.1109/JAS.2022.105746

> A new convolutional neural network is proposed for machine remaining useful life prediction.

> A series of important principles are developed for enhancing the performance of CNNs on the RUL prediction.

> A novel position encoding scheme is proposed for the RUL prediction.

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Y. M. Ju, D. R. Ding, X. He, Q.-L. Han, and G. L. Wei, “Consensus control of multi-agent systems using fault-estimation-in-the-loop: Dynamic event-triggered case,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1440–1451, Aug. 2022. doi: 10.1109/JAS.2021.1004386

> Proposed a novel consensus control framework with fault-estimation-in-the-loop for the MASs under DETP.

> Desired estimator and controller gains have been obtained in light of the solution to an algebraic matrix equation and a linear matrix inequality in a recursive way, respectively.

> A simulation result has been provided to verify the effectiveness of the proposed approach.

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M. Liu, X. Y. Zhang, M. S. Shang, and  L. Jin,  “Gradient-based differential kWTA network with application to competitive coordination of multiple robots,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1452–1463, Aug. 2022. doi: 10.1109/JAS.2022.105731

> A novel GD-kWTA network is designed, which is equipped with improved accuracy and enhanced robustness in tackling kWTA operations.

> Theorems on the convergence and robustness of the proposed network and numerical simulations in cases with or without noises are presented.

> Aided with the constructed GD-kWTA network for describing the competitive behavior, an application on the multirobot system for conducting the tracking task is provided.

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L. Chen, Z. Lin, H. Garcia de Marina, Z. Sun, and  M. Feroskhan,  “Maneuvering angle rigid formations with global convergence guarantees,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1464–1475, Aug. 2022. doi: 10.1109/JAS.2022.105749

> Aims to solve this challenging problem in both 2D and 3D under a leader-follower framework.

> Proposed angle-constrained formation maneuvering laws enable the maneuvering motions of simultaneous translation, rotation and scaling.

> Proposed 2D and 3D angle-constrained formation maneuvering laws have global convergence guarantee.

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S. F. Han, K. Zhu, M. C. Zhou, X. J. Liu, H. Y. Liu, Y. Al-Turki, and A. Abusorrah, “A novel multiobjective fireworks algorithm and its applications to imbalanced distance minimization problems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1476–1489, Aug. 2022. doi: 10.1109/JAS.2022.105752

> A new multiobjective fireworks algorithm is proposed.

> A special archive for each firework is established to guide firework explosion.

> An adaptive strategy is designed to ensure fast convergence and high solution diversity in decision space.

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L. Z. Wang, G. Xie, F. C. Qian, J. Liu, and  K. Zhang,  “A novel PDF shape control approach for nonlinear stochastic systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1490–1498, Aug. 2022. doi: 10.1109/JAS.2022.105755

> Proposed method is suitable for any nonlinear stochastic system.

> Approach is more accurate and dependable than other approximate methods.

> Can make the PDF of state response match different target PDFs.

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S. R. Nekoo, J. á. Acosta, G. Heredia, and  A. Ollero,  “A PD-type state-dependent Riccati equation with iterative learning augmentation for mechanical systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1499–1511, Aug. 2022. doi: 10.1109/JAS.2022.105533

> A nonlinear finite-time PD-like controller is presented based on SDDRE augmented with ILC.

> A convex objective function is introduced for regulation training rule of gradient descent.

> Uniform boundedness in finite time is guaranteed, suitable for unstable mechanical systems.

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L. L. Chen, L. Shi, Q. Zhou, H. M. Sheng, and Y. H. Cheng, “Secure bipartite tracking control for linear leader-following multiagent systems under denial-of-service attacks,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1512–1515, Aug. 2022. doi: 10.1109/JAS.2022.105758

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K. Zhang, Y. Liu, and J. B. Tan, “Finite-time stabilization of linear systems with input constraints by event-triggered control,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1516–1519, Aug. 2022. doi: 10.1109/JAS.2022.105761

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T. Liu, M. W. Hu, S. N. Ma, Y. Xiao, Y. Liu, and W. T. Song, “Exploring the effectiveness of gesture interaction in driver assistance systems via virtual reality,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1520–1523, Aug. 2022. doi: 10.1109/JAS.2022.105764

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C. L. Peng and J. Y. Ma, “Domain adaptive semantic segmentation via entropy-ranking and uncertain learning-based self-training,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1524–1527, Aug. 2022. doi: 10.1109/JAS.2022.105767

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Y. Liu, Y. Shi, F. H. Mu, J. Cheng, and X. Chen, “Glioma segmentation-oriented multi-modal MR image fusion with adversarial learning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1528–1531, Aug. 2022. doi: 10.1109/JAS.2022.105770

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Q. M. Cheng, Y. Z. Zhou, H. Y. Huang, and Z. Y. Wang, “Multi-attention fusion and fine-grained alignment for bidirectional image-sentence retrieval in remote sensing,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1532–1535, Aug. 2022. doi: 10.1109/JAS.2022.105773

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S. Zhang, L. Tang, and Y.-J. Liu, “Estimation based adaptive constraint control for a class of coupled string systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1536–1539, Aug. 2022. doi: 10.1109/JAS.2022.105776

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Y. J. Wang, K. Q. Li, and Z. H. Chen, “Battery full life cycle management and health prognosis based on cloud service and broad learning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1540–1542, Aug. 2022. doi: 10.1109/JAS.2022.105779