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3rd International Conference on Neural Networks, information and Communication Engineering, NNICE 2023

作者： Zheng, Xuecong Chen, Li Chen, Yaojie School of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan430065 China Wuhan Institute of Marine Electric Propulsion Hubei Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Hubei Wuhan430065 China

ISBN: (纸本)9798350335972

To solve the problem that the flame area of small targets on ships can not be easily segmented and the flame boundary is obviously affected by other background such as smoke, this experiment improves DeepLabV3+ algorithm from the following three aspects. Firstly, Dense Atrous Spatial Pyramid Pooling (DASPP) was improved to enhance the extraction and utilization of flame boundary and small target flame features. Secondly, in order to avoid the influence of background such as smoke around the flame, the high-level flame features and shallow flame features obtained by DASPP were combined with the improved Attention Mechanism (PE-SCAM) to obtain more context information in spatial and channel dimensions, so as to enhance the processing effect of the model on the flame and its boundaries. Finally, the traditional cross loss function is optimized to reduce the influence caused by the imbalance of positive and negative samples between the flame and the background. Experimental results show that the MIou of the proposed algorithm on the ship flame data set reaches 88.43%, which can realize the accurate segmentation of small target flames and flame boundaries on the basis of ensuring high real-time performance. © 2023 IEEE.

关键词： Ships

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A DoS-attack Resilient Control Approach for AIOT-enabled Systems

A DoS-attack Resilient Control Approach for AIOT-enabled Sys...

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2023 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2023

作者： Cao, Xiaoya Chen, Zhenya Liu, Weisheng Liu, Yuanlong Wang, Wenting Wang, Xin Yang, Ming Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China State Grid Shandong Electric Power Company Jinan China State Grid Shandong Electric Power Research Institute Jinan China

ISBN: (纸本)9798350312270

This paper presents a novel controller design for dealing with the challenges posed by Denial-of-Service (DoS) attacks in the context of Artificial Intelligence of Things (AIOT). The proposed design employs a prediction approach that utilizes uniform quantization for both encoder and decoder, aiming to effectively mitigate data loss during data transmission in scenarios involving DoS attacks. Furthermore, the study investigates the application of dynamic system design as a means to enhance the security defense mechanisms of AIOT, consequently bolstering the overall resilience of the system. The effectiveness and practicality of the proposed approach are validated through comprehensive simulations, providing empirical evidence of its efficacy. © 2023 IEEE.

关键词： System stability

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MTL-SRN: Multi-task Learning-based Signal Recognition Network

MTL-SRN: Multi-task Learning-based Signal Recognition Networ...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Pengxu Wang Xingjian Zhang Yuan Ma Hao Zhu Jian Jiao Qinyu Zhang Department of Electronics and Information Engineering Harbin Institute of Technology (Shenzhen) Shenzhen China Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology Harbin Institute of Technology (Shenzhen) Shenzhen China Peng Cheng Laboratory Shenzhen China State Key Laboratory of Radio Frequency Heterogeneous Integration Guangdong Key Laboratory of Intelligent Information Processing and the College of Electronic and Information Engineering Shenzhen University Shenzhen China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Wideband signal recognition is a crucial task in the cognitive wireless communication, involving accurate classification of different signal types, modulation types, center frequencies, etc. However, most conventional approaches treat the recognition of different parameters as multiple independent tasks, and often face performance bottlenecks due to the complexity and diversity of wideband signals. To overcome these challenges, we propose a multi-task learning (MTL) network that integrates multiple tasks of signal recognition into an end-to-end model to accomplish spectrum sensing, modulation recognition, and signal classification simultaneously. By employing a shared feature extraction network and a multi-task classification header, the proposed framework effectively captures the correlations and shared information among different tasks, thereby enhancing overall recognition performance. To validate the effectiveness of the proposed scheme, we compare its performance with other state-of-the-art recognition and classification networks. Experimental results demonstrate the significant performance of the proposed MTL network in spectrum sensing, modulation recognition, and signal classification tasks.

关键词： Wireless communication Correlation Accuracy Frequency modulation Face recognition Pattern classification Multitasking Sensors Global communication Wideband

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ALCencryption:A Secure and Efficient Algorithm for Medical Image Encryption

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computer Modeling in Engineering & Sciences 2020年第12期125卷 1083-1100页

作者： Jiao Ge College of Computer Science and Technology Hengyang Normal UniversityHengyang421002China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002China

With the rapid development of medical informatization and the popularization of digital imaging equipment,DICOM images contain the personal privacy of patients,and there are security risks in the process of storage and transmission,so it needs to be *** order to solve the security problem of medical images on mobile devices,a safe and efficient medical image encryption algorithm called ALCencryption is *** algorithm first analyzes the medical image and distinguishes the color image from the gray *** gray images,the improved Arnold map is used to scramble them according to the optimal number of iterations,and then the diffusion is realized by the Logistic and Chebyshev map cross-diffusion *** color image is encrypted by cross-diffusion algorithm of double chaotic *** and efficiency analysis show that the ALCencryption algorithm has the characteristics of small neighboring pixels,large key space,strong key sensitivity,high safety and short encryption *** is suitable for medical image encryption of mobile devices with high real-time requirements.

关键词： Patient privacy DICOM medical image encryption scrambling degree cross-diffusion

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Provable Discriminative Hyperspherical Embedding for Out-of-Distribution Detection 39

Provable Discriminative Hyperspherical Embedding for Out-of-...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zou, Zhipeng Wan, Sheng Li, Guangyu Han, Bo Liu, Tongliang Zhao, Lin Gong, Chen School of Computer Science and Engineering Nanjing University of Science and Technology China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education China Jiangsu Key Laboratory of Image and Video Understanding for Social Security China Hong Kong Baptist University China Sydney AI Centre The University of Sydney Sydney Australia Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

ISBN: (纸本)157735897X

Out-of-distribution (OOD) detection aims to identify the test examples that do not belong to the distribution of training data. The distance-based methods, which identify OOD examples based on their distances from the centroids of in-distribution (ID) examples, have demonstrated promising OOD detection performance. However, the objectives utilized in prior approaches are typically designed for classification and thus might not yield sufficient discriminative power to distinguish between ID and OOD examples. Therefore, this paper proposes a prototype-based contrastive learning framework for OOD detection, which is termed provable Discriminative Hyperspherical Embedding (DHE). The proposed framework provides a theoretical analysis of inter-class dispersion, which is proved to be fundamental in reducing the false positive rate (FPR) on OOD examples. Based on this, we devise an angular spread loss to achieve the maximal dispersion of the prototypes of different classes prior to training. Subsequently, a prototype-enhanced contrastive loss is introduced to align embeddings of ID examples closely with their corresponding prototypes. In our proposed DHE, the maximal prototype dispersion is theoretically proved, thereby avoiding the pitfalls of local optima commonly encountered by most existing methods. Experimental results demonstrate the effectiveness of our proposed DHE, which showcases a remarkable reduction in FPR95 (i.e., 5.37% on CIFAR-100) and more than doubling the computational efficiency when compared with the state-of-the-art methods. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Contrastive Learning

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用于紫外线成像和无线报警的水凝胶基可伸缩、高稳定性和高性能的光电传感器

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Science China Materials 2024年第6期67卷 1926-1937页

作者：洪杰钊姚帝杰王浩丁琼玲罗艺冰于家豪张鹤曾令兴杨柏儒王冰陶凯吴进 State Key Laboratory of Optoelectronic Materials and Technologies and Guangdong Province Key Laboratory of Display Material and Technology School of Electronics and Information TechnologySun Yat-sen UniversityGuangzhou 510275China Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace Northwestern Polytechnical UniversityXi’an 710072China Research&Development Institute of Northwestern Polytechnical University in Shenzhen Northwestern Polytechnical UniversityShenzhen 518063China State Key Laboratory of Transducer Technology Shanghai 200050China Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing National Engineering Research Center of Novel Equipment for Polymer ProcessingKey Laboratory of Polymer Processing Engineering(SCUT)Ministry of EducationSouth China University of TechnologyGuangzhou 510641China Engineering Research Center of Polymer Green Recycling of Ministry of Education College of Environment and ResourcesFujian Normal UniversityFuzhou 350007China State Key Laboratory of Polymer Materials Engineering Sichuan UniversityChengdu 610065China

柔性可穿戴的紫外线探测器在个体紫外线暴露监测、智能仿生眼和军事领域受到广泛关注.然而,传统不可拉伸的材料和器件结构设计限制了设备在可动态变形的人体皮肤和非平面表面上的精确监测应用和稳定附着.在本研究中,我们提出了基于氧化... 详细信息

柔性可穿戴的紫外线探测器在个体紫外线暴露监测、智能仿生眼和军事领域受到广泛关注.然而,传统不可拉伸的材料和器件结构设计限制了设备在可动态变形的人体皮肤和非平面表面上的精确监测应用和稳定附着.在本研究中,我们提出了基于氧化铜/碳-水凝胶-氧化锌/碳的新型应变隔离异质结构的本征可拉伸(拉伸应变或弯曲高达150%)紫外线探测器,该探测器具有高灵敏度(开/关比为2100%)、高稳定性(大于4000次循环),以及快速响应和恢复时间(分别为1.5和4 s).值得注意的是,该探测器通过水凝胶桥在氧化铜/碳和氧化锌/碳电极之间引入的p-n结能带结构,以及离子导电水凝胶中I^(-)/I_(3)^(-)的电化学反应机制,显著提高了其载流子效率和紫外线响应强度.本文通过集成传感器与所设计的电路板,进一步开发了一种无线紫外线报警系统,用于紫外线强度超标警报.此外,本文还设计了一种光电传感器阵列,并将其用作视网膜假体,以实现对环境紫外线强度的实时监测和成像.本文基于水凝胶基异质结构为开发可穿戴、可拉伸的光电紫外线传感器单元和成像阵列提供了一种新的可行方法.

关键词： flexible hydrogel sensors stretchable UV sensors UV imaging array optoelectronic sensors wireless alarm

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Temporal Feature Aggregation for Efficient 2D Video Grounding

Temporal Feature Aggregation for Efficient 2D Video Groundin...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Mohan Chen Yiren Zhang Jueqi Wei Yuejie Zhang Rui Feng Tao Zhang Shang Gao School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Shanghai Collaborative Innovation Center of Intelligent Visual Computing Fudan University School of Information Management and Engineering Shanghai Key Laboratory of Financial Information Technology Shanghai University of Finance and Economics School of Information Technology Deakin University

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Video grounding aims to locate the target video moment in an untrimmed video based on a text query. Most existing methods employ 3D CNNs as the video feature extractor, incurring substantial computational costs. Only a few methods use 2D backbones for video feature extraction, and they suffer from diminished accuracy due to the inherent lack of temporal information within 2D features. To address this problem, we propose a novel 2D video grounding method called TFA that improves accuracy while minimizing computational costs. Our approach involves a query-guided temporal feature aggregation module designed to explicitly capture temporal information. We disentangle time intervals of input video frames and prediction spans to reduce computational overhead. Additionally, we introduce deformable attention into the multi-modal encoder for further enhancement. Extensive experiments on two public datasets demonstrate that our method outperforms previous 2D video grounding methods and achieves competitive results with most 3D methods at significantly reduced costs.

关键词： Three-dimensional displays Accuracy Costs Grounding Streaming media Feature extraction Computational efficiency

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Unleashing Fine-Coarse Curve Perception Via Trunk-Branch Perturbation

Unleashing Fine-Coarse Curve Perception Via Trunk-Branch Per...

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IEEE International Conference on Image processing

作者： Yunxiang Cao Li Chen Yubo Wang Zhida Feng Xiaoming Liu School of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

Segmenting intricate curve structures like retinal blood vessels, encompassing both fine and coarse details, remains a significant challenge. This work proposes a novel module that divides these complex curve structures into trunks and branches, fuses the input as auxiliary information, and optimizes the breakpoints of different curve parts through losses. In order to balance the redundant information that may lead to model overfitting, a unique feature perturbation strategy is introduced after the backbone decoding process to enhance the model’s robustness to complex curve structure segmentation tasks. Experiments show that this method can effectively distinguish different topological structures of blood vessels and maintain high segmentation accuracy even at blood vessel intersections or breakpoints, which holds immense potential for diverse future applications in image segmentation.

关键词： Measurement Image segmentation Fuses Perturbation methods Blood vessels Retina Robustness

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A Probabilistic Constellation Shaping Scheme for Molecular Communications 8

A Probabilistic Constellation Shaping Scheme for Molecular C...

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8th International Conference on computer and Communication Systems, ICCCS 2023

作者： Tang, Yuankun Ji, Fei Wen, Miaowen Wang, Qianqian Chae, Chan-Byoung Yang, Lie-Liang School of Electronic and Information Engineering South China University of Technology China Guangdong Provincial Key Laboratory of Short-Range Wireless Detection and Communication China College of Computer Science and Engineering Northwest Normal University China School of Integrated Technology Yonsei University Korea Republic of School of Electronics and Computer Science University of Southampton United Kingdom

ISBN: (纸本)9781665456128

Molecular communication (MC) conveys information via chemical signals between nanomachines, which lays the foundation for the Internet of Bio-Nano Things. Based on the fact that probabilistic constellation shaping (PCS) enables reliable communication by improving energy efficiency, in this paper, we propose molecular shell mapping (MSM) to implement PCS for MC systems. The MSM method employs the concentration se-quences with the lowest sum sequence weight to construct energy-efficient signal constellations, and designs a sorting principle for sequences with the same sequence weight to mitigate inter-symbol interference (ISI). We design a Genie-aided maximum-likelihood (ML) detector and a realistic ML detector to leverage the constructive effect of ISI from the current concentration sequence, and derive their achievable rates. Numerical simulation results confirm that the shaped signaling using the MSM method is more energy-efficient than the equiprobable signaling, achieving an up to 1.5 dB gain at an ultra-short blocklength. © 2023 IEEE.

关键词： Numerical methods

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FlyLISL: Traffic Balance Awared Routing for Large-scale Mixed-Reality Telepresence over Reconfigurable Mega-Constellation 42

FlyLISL: Traffic Balance Awared Routing for Large-scale Mixe...

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42nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2022

作者： Zhang, Ruoyi Deng, Jing Liu, Qi Xie, Xinlei Gong, Qingyuan Zhu, Chao Beijing Institute of Technology School of Cyberspace Science and Technology China Communication University of China State Key Laboratory of Media Convergence and Communication China School of Information and Electronics Beijing Institute of Technology China School of Computer Science Fudan University Shanghai Key Lab of Intelligent Information Processing China

ISBN: (数字)9781665488792

ISBN: (纸本)9781665488792

With the emerging telepresence applications, such as meta universe, tele-education and tele-social, there exist a large number of demands for sufficient network resources for visual streaming. However, transmitting the huge volume of the generated visual data through the meandering terrestrial networks would overwhelm the backbone networks and cause non-negligible latency. Mega-constellations, such as OneWeb and Starlink, is developing as one of 'New Infrastructure Construction', and could provide high-capacity and low-latency communication in a world-wide range. However, most of the existing mega-constellation networks' topology is fixed and would easily fall into congestion with the bursting traffic generated by the large-scale telepresence applications. To address this challenge, we propose a reconfigurable mega-constellation architecture by utilizing the permanent and temporary laser inter-satellite links (LISLs). Moreover, based on the mixed-integer linear programming (MILP), we design a routing system, FlyLISL, aiming at balancing the global traffic load by minimizing the maximum link utilization of all LISLs. To evaluate the effectiveness of FlyLISL, we simulate the performance of FlyLISL by comparing with the particle swarm optimization (PSO) and Random based routing strategies. Compared with reference works, FlyLISL reduces the maximum link utilization by up to 72.6%. © 2022 IEEE.

关键词： Mixed reality

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