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第41届中国控制会议

作者： Binghe An Zongzhun Zheng Bo Wang Huijin Fan Lei Liu Yongji Wang National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and AutomationHuazhong University of Science and Technology Beijing Aerospace Automatic Control Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,we focus on the time-to-go estimation problem for the impact-angle-constrained guidance *** facilitate the time-to-go estimation,the whole guidance process is divided into two *** sliding mode guidance law based on the constant reaching law is designed for the first stage and the proportional guidance law is utilized in the second *** choosing the sliding mode variable appropriately,not only an attack with a small miss distance but also a prescribed impact angle can be *** to the feature of the constant reaching law,the time-to-go estimation for the first stage can be established *** obtain the time-to-go of the second stage,the estimated look-ahead angle and range at the switching point between the first stage and second stage are ***,the time-to-go estimation of the second stage is obtained according to the trajectory shape of the missile steered by the proportional guidance *** the second stage,rather than the estimated look-ahead angle and range but the current look-ahead angle and range are used to calculate the *** this way,an actual time-to-go estimation of the second stage can be ***,various numerical simulations are provided to show the effectiveness and superiority of the proposed estimation scheme.

关键词： Time-to-go estimation Impact angle constraint Sliding mode guidance law Two-stage guidance law

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Multi-View Graph Embedding Learning for Image Co-Segmentation and Co-Localization

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IEEE Transactions on Circuits and Systems for Video technology 2024年第6期34卷 4942-4956页

作者： Huang, Aiping Li, Lijian Zhang, Le Niu, Yuzhen Zhao, Tiesong Lin, Chia-Wen Fuzhou University Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering Fuzhou350108 China Fuzhou University Fujian Key Laboratory of Network Computing and Intelligent Information Processing College of Computer and Data Science Fuzhou350108 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Fuzhou University Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering The Fujian Science and Technology Innovation Laboratory for Optoelectronic Information Fuzhou350108 China Institute of Communications Engineering National Tsing Hua University Department of Electrical Engineering Hsinchu30013 Taiwan

Image co-segmentation and co-localization exploit inter-image information to identify and extract foreground objects with a batch mode. However, they remain challenging when confronted with large object variations or complex backgrounds. This paper proposes a multi-view graph embedding (MV-Gem) learning scheme which integrates diversity, robustness and discernibility of object features to alleviate this phenomenon. To encourage the diversity, the deep co-information containing both low-layer general representations and high-layer semantic information is generated to form a multi-view feature pool for comprehensive co-object description. To enhance the robustness, a multi-view adaptive weighted learning is formulated to fuse the deep co-information for feature complementation. To ensure the discernibility, the graph embedding and sparse constraint are embedded into the fusion formulation for feature selection. The former aims to inherit important structures from multiple views, and the latter further selects important features to restrain irrelevant backgrounds. With these techniques, MV-Gem gradually recovers all co-objects through optimization iterations. Extensive experimental results on real-world datasets demonstrate that MV-Gem is capable of locating and delineating co-objects in an image group. © 1991-2012 IEEE.

关键词： Semantics

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An electronically controlled hyperspectral infrared Fabry-Perot filter based on the Fano effect 3

An electronically controlled hyperspectral infrared Fabry-Pe...

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3rd International Conference on Optics and Image processing, ICOIP 2023

作者： Chen, Zhaomin Gao, Zecheng Zhang, Xinyu National Key Laboratory of Science & Technology on Multispectral Information Processing Huazhong University of Science & Technology Hubei Wuhan430074 China School of Artificial Intelligence and Automation Huazhong University of Science & Technology Hubei Wuhan430074 China

ISBN: (纸本)9781510667426

This paper introduces the design and experiments of a new electrically controlled hyperspectral infrared Fabry-Perot (FP) filter based on Fano resonance. The FP filter reflector material is studied and the DBR layer film system structure is selected for simulation calculations. Ge material is selected for the high refractive index layer and SiO2 material is selected for the low refractive index layer. The dentate structure hyperspectral infrared FP filter is designed by studying the principle of symmetry breaking to produce Fano resonance. The filter transmission spectrum is simulated and calculated using finite element simulation software. Mathematical modeling of the liquid crystal layer is performed to iteratively calculate the variation of the equivalent refractive index of the liquid crystal under different applied voltages. A bilaterally symmetric single-dentete structure filter with liquid crystal filling in the middle was made to test the variation of the transmission spectrum by applying different voltages to verify the correctness of the *** results show that the appearance of a significant Fano resonance peak is observed in the designed device, implying that the design objectives are well achieved. © 2023 SPIE. All rights reserved.

关键词： Liquid crystals

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Design of polarimetric camera based on the single-layer twisted nematic liquid crystal device 12

Design of polarimetric camera based on the single-layer twis...

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SPIE 12th International Symposium on multispectral Image processing and Pattern Recognition, MIPPR 2023

作者： Ye, Mao Zhu, Wenjie Liu, Kewei Zhang, Xinyu Institude of Artificial Intelligence Huazhong University of Science and Technology Hubei Wuhan430074 China National Key Laboratory of Science & Technology on Multispectral Information Processing Huazhong University of Science & Technology Wuhan430074 China School of Artificial Intelligence & Automation Huazhong University of Science & Technology Wuhan430074 China

ISBN: (数字)9781510674929

ISBN: (纸本)9781510674912

Polarization is the asymmetry of a light wave's electric field vibration direction with respect to its propagation direction, as a crucial clue for describing the light, which is one of the most apparent signs that distinguishes transverse waves from longitudinal waves. The current mainstream polarimetric cameras typically adopt a division of focal plane imaging architecture, in which a metal wire-grid structure is coupled with a detector to acquire the polarization state of the target. However, the structure of the division of focal plane reduces effective spatial resolution of the detector and requires complex registration algorithms to achieve pixel-level polarization acquisition, which leads to high equipment costs and impedes the development and application of polarimetric cameras in industrial production. In this paper, a single-layer twisted nematic liquid crystal (TNLC) is inserted to the imaging optical path of traditional camera to realize the polarization acquisition, allowing for a cost-effective transition from traditional devices to polarization imaging systems. The imaging detector coupled with the TNLC device can acquire polarization states ranging from 10 to 90-degree by adjusting the external voltage applied on the LC device. Moreover, a polarization angle calibration method based on a single-layer TNLC is proposed in this paper, providing a reliable reference for electrically controlled polarization angle acquisition. The experimental results acquired by presented imaging system demonstrate the feasibility and effectiveness of the proposed method. The TNLC based imaging scheme presented in this paper provides a solid foundation for developing simple, low-cost, and efficient polarimetric cameras. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Cameras

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From First-Order to Second-Order Rationality: Advancing Game Convergence with Dynamic Weighted Fictitious Play

arXiv

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arXiv 2024年

作者： Ju, Qi Hei, Falin Liu, Yuxuan Fang, Zhemei Luo, Yunfeng Huazhong University of Science and Technology China National Key Laboratory of Science and Technology on Multispectral Information Processing China

Constructing effective algorithms to converge to Nash Equilibrium (NE) is a important problem in algorithmic game theory. Prior research generally posits that the upper bound on the convergence rate for games is O ( T−1/2). This paper introduces a novel perspective, positing that the key to accelerating convergence in game theory is "rationality". Based on this concept, we propose a Dynamic Weighted Fictitious Play (DW-FP) algorithm. We demonstrate that this algorithm can converge to a NE and exhibits a convergence rate of O(T−1) in experimental evaluations. © 2024, CC BY.

关键词： Consensus algorithm

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Data secure transmission intelligent prediction algorithm for mobile industrial IoT networks

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Digital Communications and Networks 2023年第2期9卷 400-410页

作者： Lingwei Xu Hao Yin Hong Jia Wenzhong Lin Xinpeng Zhou Yong Fu Xu Yu Department of Information Science and Technology Qingdao University of Science and TechnologyQingdao266061China Fujian Key Laboratory of Sensing and Computing for Smart Cities Xiamen UniversityXiamen361005China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control(Minjiang University) Fuzhou350121China Faculty of Information Science and Engineering Ocean University of ChinaQingdao266100China Shandong Provincial Key Laboratory of Computer Networks Shandong Computer Science Center(National Supercomputer Center in Jinan)JinanChina

Mobile Industrial Internet of Things(IIoT)applications have achieved the explosive growth in recent *** mobile IIoT has flourished and become the backbone of the industry,laying a solid foundation for the interconnection of all *** variety of application scenarios has brought serious challenges to mobile IIoT networks,which face complex and changeable communication *** data secure transmission is critical for mobile IIoT *** paper investigates the data secure transmission performance prediction of mobile IIoT *** cut down computational complexity,we propose a data secure transmission scheme employing Transmit Antenna Selection(TAS).The novel secrecy performance expressions are first ***,to realize real-time secrecy analysis,we design an improved Convolutional Neural Network(CNN)model,and propose an intelligent data secure transmission performance prediction *** mobile signals,the important features may be removed by the pooling *** will lead to negative effects on the secrecy performance prediction.A novel nine-layer improved CNN model is *** of the input and output layers,it removes the pooling layer and contains six convolution ***,Back-Propagation(BP)and LeNet methods are employed to compare with the proposed *** simulation analysis,good prediction accuracy is achieved by the CNN *** prediction accuracy obtains a 59%increase.

关键词： Mobile IIoT networks Data secure transmission Performance analysis Intelligent prediction Improved CNN

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Point Clouds Registration Algorithm Based on Spatial Structure Similarity of Visual keypoints 16th

Point Clouds Registration Algorithm Based on Spatial Structu...

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16th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2021

作者： Gao, Yingshuo Ma, Jie Wu, Bingli Zhang, Tianxiang Yang, Yu National Key Laboratory of Multispectral Information Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789811912528

In autonomous driving technology, vehicles use LiDAR to accomplish various tasks. Issues are that the point cloud collected by the LiDAR is too sparse and some objects are mutilated, which is a great challenge for tasks such as detection and recognition. It is necessary to merge multiple frames of point clouds with registration algorithm to make data complete and dense. Previous point cloud registration methods run slowly and have low accuracy when dealing with autopilot field point clouds. It is difficult to find the correspondence of different point clouds. While humans can easily find the exact corresponding through the visual information received by eyes, as it contains color and texture. The visual images acquired by optical cameras can simulate the human eyes well. Therefore, we propose to use visual image assisted point cloud registration. Firstly, we extract the keypoints of visual images, then we obtain their depth by depth completion algorithm and back-project them into 3D space as 3D keypoints. Finally, we screen 3D keypoint pairs by spatial structure similarity to estimate the rigid transformation parameters. After experiments, it is proved that our method achieves substantial improvement in both speed and accuracy. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Optical radar

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Accelerating nash equilibrium convergence in Monte Carlo settings through counterfactual value based fictitious play 24

Accelerating nash equilibrium convergence in Monte Carlo set...

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Proceedings of the 38th International Conference on Neural information processing Systems

作者： Ju Qi Hei Falin Feng Ting Yi Dengbing Fang Zhemei Luo Yunfeng School of Artificial Intelligence and Automation Huazhong University of Science and Technology and National Key Laboratory of Science and Technology on Multispectral Information Processing

ISBN: (纸本)9798331314385

Counterfactual Regret Minimization (CFR) and its variants are widely recognized as effective algorithms for solving extensive-form imperfect information games. Recently, many improvements have been focused on enhancing the convergence speed of the CFR algorithm. However, most of these variants are not applicable under Monte Carlo (MC) conditions, making them unsuitable for training in large-scale games. We introduce a new MC-based algorithm for solving extensive-form imperfect information games, called MCCFVFP (Monte Carlo Counterfactual Value-Based Fictitious Play). MCCFVFP combines CFR's counterfactual value calculations with fictitious play's best response strategy, leveraging the strengths of fictitious play to gain significant advantages in games with a high proportion of dominated strategies. Experimental results show that MCCFVFP achieved convergence speeds approximately 20%~50% faster than the most advanced MCCFR variants in games like poker and other test games.

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Dual-mimic learning for occluded pedestrian detection 1

Dual-mimic learning for occluded pedestrian detection

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1st International Conference on Mechanics, Electronics, Automation and Automatic Control, MEAAC 2023

作者： Pan, Xiaofeng Han, Shoudong Ding, Huilin Wang, Yukun National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Engineering and Applied Science Columbia University NY10027 United States

It is still a great challenge to detect pedestrians in crowded scenes. Recent works mainly focus on enhancing the feature representation of the visible region. Although this strategy is effective, it fails to fully exploit the appearance information contained in the full-body region. To this end, we propose a Dual-Mimic learning model, which consists of the occluded to unoccluded (Occ-Unocc) and the full-body to visible (Full-Vis) mimic learning branches. Both branches can reduce the intra-class feature variances of pedestrians by different mimicking strategies. Besides, we define an occlusion attribute to describe the occlusion pattern of each detection. Based on the occlusion attribute, we propose the Occlusion-aware NMS (Occ-NMS), which can effectively remain the occluded instance with low confidence. We conduct extensive experiments on standard benchmarks of CityPersons and Caltech, and our method achieves a new state-of-the-art performance at 36.34% MR-2 and 25.07% MR-2 on heavy occlusion sets. © Published under licence by IOP Publishing Ltd.

关键词： Benchmarking

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Distribution Mining and Noise Correction for Facial Expression Recognition 5

Distribution Mining and Noise Correction for Facial Expressi...

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5th International Conference on Computer Vision, Image and Deep Learning, CVIDL 2024

作者： Huang, Hailan Tan, Yihua Huazhong University of Science and Technology National Key Laboratory of Science & Technology on Multi-spectral Information Processing School of Artificial Intelligence and Automation Wuhan430074 China

ISBN: (纸本)9798350373820

Due to the high annotation cost and inter-class ambiguity, many facial expression datasets only offer noisy one-hot labels. This creates two challenges for facial expression recognition (FER) as the one-hot labels only represent limited single semantics, and the noisy labels will mislead the model. Our study proposes a novel method to perform both label Distribution Mining and Noise Correction (DMNC) on the FER dataset. That is, while eliminating the disturbance of noisy samples, we start from the original one-hot labels and gradually refine them to distributions of expressions close to the real world. Specifically, DMNC uses the network forgetting property to select noisy samples. Then based on clean samples, an expression feature space is learned by contrastive learning. Finally, the labels of clean and noisy samples are refined or relabelled in a divide-and-conquer manner using the learned feature space. Experiments show that our method exhibits leading performance on both real-world FER benchmarks and synthetic noisy datasets. © 2024 IEEE.

关键词： Semantics

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