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第43届中国控制会议

作者： Chicheng Huang Chuandong Li Zelin Gao Zhenyu Wu Yawei Shi Huaqing Li College of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The increasing use of millimeter wave radar for smart elderly care is due to its precision,privacy,and *** technology enables real-time monitoring of unexpected incidents,particularly falls among the elderly *** examining the relationship between cloud points and human centroids,this paper exploits the unique features of millimeter wave radar for personnel detection and human activity *** improved Kalman filter algorithm for centroid tracking has been *** effectively monitors the three-dimensional trajectory and velocity changes associated with various human ***,machine learning algorithms and neural networks are employed to classify these behaviors,including walking,sitting,and *** to conventional Kalman filtering,this approach effectively handles dispersion characteristics within point clouds,resulting in a smoother trajectory and more consistent *** method enables the recognition of abnormal activities of people indoors with a maximum classification accuracy of 93.02%.

关键词： Millimeter Wave Radar Point Clouds Centroid Tracking Human Activity Recognition

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Uniform Solution to QSAT by P Systems with Proteins

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Chinese Journal of Electronics 2023年第4期21卷 667-672页

作者： Chun LU Xiaolong SHI Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

P systems are distributed parallel computing models in the area of membrane computing, which are inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order structures. P systems with proteins on membranes are a class of P systems, which have proved to be very efficient computing devices. Specifically, it was known that the Quantified satisfiability problem (QSAT) of a Boolean formula can be solved by a semi-uniform family of P systems with proteins on membranes and with membrane division. However, it remains open whether a uniform families of P systems with proteins on membranes can solve in polynomial time exactly the class of problems PSPACE. In this work, we present a uniform solution to QSAT problem by P systems with proteins on membranes in a linear time with respect to both the number $n$ of Boolean variables and the number $m$ of clauses of the instance, which answers the above open problem.

关键词： Proteins Image processing Computational modeling Organizations Parallel processing intelligent control

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EMOST: A dual-branch hybrid network for medical image fusion via efficient model module and sparse transformer

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Computers in Biology and Medicine 2024年 179卷 108771-108771页

作者： Wang, Wenqing He, Ji Liu, Han School of Automation and Information Engineering Xi'an University of Technology Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China

Multimodal medical image fusion fuses images with different modalities and provides more comprehensive and integrated diagnostic information. However, current multimodal image fusion methods cannot effectively model non-local contextual feature relationships, and due to direct aggregation of the extracted features, they introduce unnecessary implicit noise into the fused images. To solve the above problems, this paper proposes a novel dual-branch hybrid fusion network called EMOST for medical image fusion that combines a convolutional neural network (CNN) and a transformer. First, to extract more comprehensive feature information, an effective feature extraction module is proposed, which consists of an efficient dense block (EDB), an attention module (AM), a multiscale convolution block (MCB), and three sparse transformer blocks (STB). Meanwhile, a lightweight efficient model (EMO) is used in the feature extraction module to exploit the efficiency of the CNN with the dynamic modeling capability of the transformer. Additionally, the STB is incorporated to adaptively maintain the most useful self-attention values and remove as much redundant noise as possible by developing the top-k selection operator. Moreover, a novel feature fusion rule is designed to efficiently integrate the features. Experiments are conducted on four types of multimodal medical images. The proposed method shows higher performance than the art-of-the-state methods in terms of quantitative and qualitative evaluations. The code of the proposed method is available at https://***/XUTauto/EMOST. © 2024 Elsevier Ltd

关键词： Feature extraction

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Whale optimisation algorithm with role labour division for multimodal optimisation

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International Journal of Innovative Computing and Applications 2024年第1期15卷 26-37页

作者： Wu, Bowen Xiao, Renbin School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan430074 China Institute of Artificial Intelligence Huazhong University of Science and Technology Hubei Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Ministry of Education of China Huazhong University of Science and Technology Hubei Wuhan430074 China

The multimodal optimisation problem challenges the balance between diversity and convergence, which poses a great degree of challenge to traditional population-based intelligence optimisers. The whale optimisation algorithm has the limitation of easily falling into local optimum when facing multimodal optimisation. To address this problem, this paper proposes a whale optimisation algorithm with role labour division (WOA-RDL). In WOA-RDL, a multi-stage role division of labour mechanism is designed to divide the optimisation process into two stages of group hunting. In the first stage, the task allocation in the hunting process is considered as two types of search tasks: exploration and exploitation. The external environmental stimulus of the task and the internal response threshold of the individual were designed to allow individuals to switch between exploration and exploitation tasks flexibly. In the second stage, the distribution mechanism of different roles was designed to simulate the 'strong to weak' distribution rule for the distribution of results after the hunt. The elite roles are selected to further strengthen their capabilities or remain robust, while the inferior roles are predicted and eliminated to improve the overall optimisation of the population and reduce the risk of falling into a local optimum. The results of the optimisation experiments using multimodal, unimodal, CEC2017 combined functions and CEC2009 dynamic functions to validate the effectiveness of the algorithm. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Optimization algorithms

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Layer-Specific Scaling of Positional Encodings for Superior Long-Context Modeling

arXiv

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arXiv 2025年

作者： Wang, Zhenghua Ding, Yiran Lv, Changze Xu, Zhibo Li, Tianlong Shi, Tianyuan Zheng, Xiaoqing Huang, Xuanjing Fudan University China Westlake University China Shanghai Key Laboratory of Intelligent Information Processing China

Although large language models (LLMs) have achieved significant progress in handling long-context inputs, they still suffer from the "lost-in-the-middle" problem, where crucial information in the middle of the context is often underrepresented or lost. Our extensive experiments reveal that this issue may arise from the rapid long-term decay in Rotary Position Embedding (RoPE). To address this problem, we propose a layer-specific positional encoding scaling method that assigns distinct scaling factors to each layer, slowing down the decay rate caused by RoPE to make the model pay more attention to the middle context. A specially designed genetic algorithm is employed to efficiently select the optimal scaling factors for each layer by incorporating Bézier curves to reduce the search space. Through comprehensive experimentation, we demonstrate that our method significantly alleviates the "lost-in-the-middle" problem. Our approach results in an average accuracy improvement of up to 20% on the key-Value Retrieval dataset. Furthermore, we show that layer-specific interpolation, as opposed to uniform interpolation across all layers, enhances the model’s extrapolation capabilities when combined with PI and Dynamic-NTK positional encoding schemes. Copyright © 2025, The Authors. All rights reserved.

关键词： Rope

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Research on Dataset Preparation and Registration Methods for Multi-Temporal Airport SAR Images 2

Research on Dataset Preparation and Registration Methods for...

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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Wu, Guanghui Liu, Lujiao Li, Jianhao Pan, Hongxin Shi, Hao Beijing Institute of Technology Chongqing Innovation Center Chongqing China Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Beijing Institute of Technology National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing China

ISBN: (纸本)9798331515669

Synthetic Aperture Radar (SAR) offers high-resolution imaging capabilities that are unaffected by weather and lighting conditions, making it ideal for complex environments. Recent advancements in spaceborne SAR technology have provided diverse high-resolution, multi-temporal SAR data, crucial for applications like airport monitoring. Despite these advancements, there is a notable lack of multi-temporal airport SAR datasets for research. This study addresses this gap by presenting a method to create a multi-temporal airport SAR image dataset. Utilizing known latitude and longitude information, the method converts geographic coordinates to image projection coordinates to locate airports in SAR images, followed by image conversion and alignment to construct the dataset. Additionally, this study introduces a registration method named SAR-SURF for multi-temporal SAR images, employing a SURF-based Feature Points Detector and an improved Fast Sample Consensus (FSC) algorithm. The experimental results demonstrate that this method effectively reduces speckle noise, ensures matching accuracy, and minimizes processing time, enabling rapid and precise registration of multi-temporal airport SAR images. © 2024 IEEE.

关键词： Image registration

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DASC-SPT: Towards Self-Supervised Panoramic Semantic Segmentation

DASC-SPT: Towards Self-Supervised Panoramic Semantic Segment...

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2025 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2025

作者： Tan, Tianlong Chen, Bin Cao, Hongliang Yan, Chenggang Ma, Yike Dai, Feng Institute of Computing Technology Chinese Academy of Sciences Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences Beijing China Shandong University China University of Chinese Academy of Sciences Beijing China Hangzhou Dianzi University China

ISBN: (纸本)9798331510831

Self-Supervised Semantic Segmentation, aiming to leverage masses of unlabeled data for boosting semantic segmentation, has been rapidly emerging as an active task in recent years. However, existing self-supervised semantic segmentation approaches mainly focus on planar images, leaving multiple distorted objects encountered in panoramic images unexplored due to the formidable challenge of handling heterogeneous degrees of distortions across different locations. In this paper, we propose a novel Self-Supervised Panoramic Semantic Segmentation model, termed DASC-SPT, built upon the mainstream contrastive learning framework. Towards distortions in panoramic images, we present two structures to better learn from distorted features by applying planar images. For the input images of self-supervision, we design a Spherical Projection Transformation (SPT) strategy that involves randomly projecting planar images onto various locations of the sphere to introduce the distortions. For pixel-wise distorted features, we construct a Deformation-aware Sampling Consistency (DASC) framework to further utilize the shared content and discrepancies caused by different distortions of paired views, where the deformation-aware consistency can be quantified on pixel-wise features. Both of the two components facilitate the model to adapt to distortions and boost panoramic semantic segmentation. Extensive comprehensive experiments on three panoramic datasets demonstrate the effectiveness and superiority of DASC-SPT approach. © 2025 IEEE.

关键词： Semantic Segmentation

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Discrimination of wheat unsound grains based on deep learning and terahertz spectral image technology 17

Discrimination of wheat unsound grains based on deep learnin...

引用

17th National Conference on Laser Technology and Optoelectronics

作者： Wang, Fei Jiang, Yuying Ge, Hongyi Chen, Xinyu Li, Li Key Laboratory of Grain Information Processing & Control Ministry of Education Henan University of Technology Zhengzhou450001 China

ISBN: (纸本)9781510661097

The problem of insignificant image features and poor image quality in the acquisition of terahertz spectral images of unsound wheat. Therefore, this study proposed the FFDNet-VGG terahertz image enhancement algorithm based on the FFDNet denoising algorithm and VGG feature extraction algorithm. The experimental results showed that this algorithm could effectively improve the image quality compared with the traditional algorithms such as BM3D and WNNM, and the PSNR and SSIM of the enhanced images were 39.10 dB and 0.93, respectively. The wheat unsound grain images processed by FFDNet, VGG and FFDNet-VGG algorithms were verified by CNN classification network with the classification accuracy of 93.1% and 93.7%, respectively. FFDNet-VGG effectively enhances the wheat unsound grain terahertz spectral images. © 2022 SPIE.

关键词： Image denoising

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Imperceptible and Sparse Adversarial Attacks via a Dual-Population-Based Constrained Evolutionary Algorithm

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第2期4卷 268-281页

作者： Tian, Ye Pan, Jingwen Yang, Shangshang Zhang, Xingyi He, Shuping Jin, Yaochu Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Hefei230601 China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei230088 China Anhui University School of Computer Science and Technology Hefei230601 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Hefei230601 China Anhui University Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and Automation Hefei230601 China Bielefeld University Faculty of Technology Bielefeld33619 Germany

The sparse adversarial attack has attracted increasing attention due to the merit of a low attack cost via changing a small number of pixels. However, the generated adversarial examples are easily detected in vision since the perturbation to each pixel is relatively large. To achieve imperceptible and sparse adversarial attacks, this article formulates a bi-objective constrained optimization problem, simultaneously minimizing the 0 and 2 distances to the original image, and proposes a dual-population-based constrained evolutionary algorithm to solve it. The proposed method solves the optimization problem by evolving two populations, where one population is responsible for finding feasible solutions (i.e., successful attacks) and the other one is to minimize both the 0 and 2 distances. Moreover, a population initialization strategy and two genetic operators are customized to accelerate the convergence speed. Experimental results indicate that the proposed method can achieve high success rates with low attack costs, and strikes a better balance between the 0 and 2 distances than state-of-the-art methods. © 2020 IEEE.

关键词： Evolutionary algorithms

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Weighting Strategy of Multi-camera System for Pose Measurement

Weighting Strategy of Multi-camera System for Pose Measure...

引用

International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Li, Yuran Zhou, Tongyuehao Yu, Wenbin Li, Yichen Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9789811966125

In a multi-camera system, based on Binocular vision, choosing the best camera combination is one of the effective ways to improve measurement accuracy. When multi-cameras layout and intrinsic parameters are fixed, the angle and the distance from cameras to object are two main factors influencing the pose measurement result. From the perspective of object’s observability and image resolution, the mathematic relation between measurement error and the angle, distance from cameras to object is derived which forms the weighting formula whose high value corresponds to the best camera combination. Comprehensive simulation is conducted, proving that the proposed method can decrease the measurement error by 55% compared with former methods, and even by 94% in some occasions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cameras

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