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EK-Net++: Real-time scene text detection with expand kernel distance and Epoch Adaptive Weight

Expert Systems with Applications 2025年 267卷

作者： Zhu, Boyuan Chen, Xi Tang, Quan Chen, C.L. Philip Liu, Fagui Computer Science and Engineering South China University of Technology Guangzhou510006 China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen518066 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Recently, scene text detection has received significant attention due to its wide applications. Accurate detection in complex scenes of multiple scales, orientations, and curvature remains a challenge. Component-based methods have emerged as the dominant approach for offering a more flexible way to achieve superior performance. However, Component-based methods employ the Vatti clipping algorithm for multi-instance training to handle the difficulty of arbitrary-shaped text. Yet we identify several bias results from these approaches called the "shrinked kernel" leading to decreased accuracy. Additionally, almost all text detection methods fail to consider the characteristics of different datasets and directly assign fixed loss weights to multi-instances. To address these limitations, we propose a new approach named Expand Kernel Network (EK-Net++), which presents the expand kernel distance map to compensate for the previous deficiency and incorporates three-stage regression to complete integral instance detection. Furthermore, we design the Epoch Adaptive Weight algorithm which dynamically distinguishes the characteristics of different datasets. EK-Net++ not only achieves precise positioning of arbitrary-shaped text but also strikes a balance between performance and speed. Evaluation results show that EK-Net++ attains state-of-the-art or competitive performance compared to other advanced methods, e.g., F-measure of 86.72% at 35.42 FPS on ICDAR 2015, F-measure of 85.83% at 40.13 FPS on CTW1500. © 2024 Elsevier Ltd

关键词： Epoch Adaptive Weight Expand kernel distance Real-time Scene text detection

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Estimating the Reliability of a DApps-Based Files Storage System

Estimating the Reliability of a DApps-Based Files Storage Sy...

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International Russian Automation Conference (RusAutoCon)

作者： Obadah Hammoud Ivan A. Tarkhanov Engineering Cybernetics Research Faculty National University of Science and Technology Moscow Russia Federal Research Center “Computer Science and Control” of Russian Academy of Sciences State Academic University for Humanities Moscow Russia

One of the key features of blockchain is high reliability, due to its high redundancy nature. While creating many replications across nodes serves well for storing relatively small data entries, this cannot be used with big files, as it might be impossible to replicate many huge files across many nodes. Here we present a DApps-based system that can lead to improving the total reliability of distributed files storage systems by managing the internal processes using DApps instead of a classical centralized load balancer. For the same reason, known reliability calculation methods for distributed file storage systems are not suitable for assessing the reliability of DApps-based systems. They do not take into account the automatic recovery time of files. In this article, we will deduce the reliability method for DApps-based system, then compare the resulting reliability with other existing systems, and discuss the benefits gained in total.

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QoE-oriented Soft Caching with Content Recommendation for Edge Computing Networks

QoE-oriented Soft Caching with Content Recommendation for Ed...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Chenyang Wang Yan Chen Chuan Sun Bosen Jia Xiaofei Wang Tarik Taleb Victor C. M. Leung College of Computer Science & Software Engineering Shenzhen University Shenzhen China Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) Shenzhen China Faculty of Electrical Engineering and Information Technology Ruhr University Bochum Bochum Germany College of Computing and Data Science Nanyang Technological University Singapore China Unicom Digital Technology Co. Ltd Beijing China College of Intelligence and Computing Tianjin University Tianjin China University of British Columbia Vancouver Canada

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Mobile Edge Caching (MEC) can potentially alleviate Internet transmission congestion by delivering content at the network edge. However, current MEC solutions suffer from low resource utilization efficiency and often fail to meet user Quality of Experience (QoE), primarily due to dynamic user requests and obsessive pursuit of direct caching hits. Given the prevalence of recommendation systems, users often lack precise requests when using recommendation-based applications like TikTok and Taobao, insted passively enjoying recommended content. In this paper, we introduce a recommendation-enabled MEC architecture to enhance resource utilization and QoE. We develop a recommendation-enabled soft caching model and formulate the optimization problem as maximizing joint system revenue. To address this, we propose an attention-assisted federated learning deep Q-network algorithm. We conduct the simulations by using the real-world MIND dataset. The results demonstrate that our proposed algorithm outperforms existing baselines, demonstrating its effectiveness in improving resource utilization and QoE.

关键词： Video on demand Heuristic algorithms Computational modeling Internet Quality of experience Resource management Web sites Global communication Optimization Recommender systems

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Applications of MXenes in human-like sensors and actuators

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Nano Research 2023年第4期16卷 5767-5795页

作者： Jinbo Pang Songang Peng Chongyang Hou Xiao Wang Ting Wang Yu Cao Weijia Zhou Ding Sun Kai Wang Mark H.Rümmeli Gianaurelio Cuniberti Hong Liu Institute for Advanced Interdisciplinary Research(iAIR) Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of ShandongUniversity of JinanJinan 250022China Institute for Materials Science and Max Bergmann Center of Biomaterials Technische Universität DresdenDresden 01069Germany Center for Advancing Electronics Dresden Technische Universität DresdenDresden 01069Germany Dresden Center for Computational Materials Science Technische Universität DresdenDresden 01062Germany Dresden Center for Intelligent Materials(GCL DCIM) Technische Universität DresdenDresden 01062Germany High-Frequency High-Voltage Device and Integrated Circuits R&D Center Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Microelectronic Devices&Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China State Key Laboratory of Biobased Material and Green Papermaking Qilu University of TechnologyShandong Academy of SciencesJinan 250353China School of Bioengineering Qilu University of TechnologyShandong Academy of ScienceJinan 250353China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology(Ministry of Education) Northeast Electric Power UniversityJilin 132012China School of Electrical Engineering Northeast Electric Power UniversityJilin 132012China School of Electrical Engineering Weihai Innovation Research InstituteQingdao UniversityQingdao 266000China School of Electrical and Computer Engineering Jilin Jianzhu UniversityChangchun 130118China Institute for Complex Materials Leibniz Institute for Solid State and Materials Research Dresden(IFW Dresden)20 Helmholtz StrasseDresden 01069Germany College of Energy Soochow Institute for Energy and Materials Innovations Soochow UniversitySuzhou 215006China Key L

Human beings perceive the world through the senses of sight,hearing,smell,taste,touch,space,and *** first five senses are prerequisites for people to *** sensing organs upload information to the nervous systems,including the brain,for interpreting the surrounding ***,the brain sends commands to muscles reflexively to react to stimuli,including light,gas,chemicals,sound,and ***,as an emerging two-dimensional material,has been intensively adopted in the applications of various sensors and *** this review,we update the sensors to mimic five primary senses and actuators for stimulating muscles,which employ MXene-based film,membrane,and composite with other functional ***,a brief introduction is delivered for the structure,properties,and synthesis methods of ***,we feed the readers the recent reports on the MXene-derived image sensors as artificial retinas,gas sensors,chemical biosensors,acoustic devices,and tactile sensors for electronic ***,the actuators of MXene-based composite are ***,future opportunities are given to MXene research based on the requirements of artificial intelligence and humanoid robot,which may induce prospects in accompanying healthcare and biomedical engineering applications.

关键词： MXenes sensors actuators gas sensors biosensors tactile sensors sound sensors artificial retina

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Sinusoidal-Assisted Synchrosqueezing Transform: Algorithms and Biomedical Applications

SSRN

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SSRN 2022年

作者： Chen, Tao Zheng, Qian Xie, Lei Su, Hongye State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China College of Computer Science and Control Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Hangzhou Flexolink Technology Co. Ltd. Hangzhou China

Intermittent oscillation signals (IOSs) exist widely in biomedical systems. They are always contaminated by various randomness like noise and artifacts. Compared with traditional time-frequency analysis (TFA) methods, adaptive TFA methods show the significant advantages in separating IOSs. However, these methods are implemented by assuming that the input signal is in a weakly noisy environment and have narrow-band limitation for extracting IOSs. Besides, it is difficult for these methods to alleviate the noise in the gap among times where IOSs happen. Therefore, in this paper, a new method called the sinusoidal-assisted synchrosqueezing transform (SASST) is proposed for separating IOSs in strongly noisy environment. The SASST method locates the IOSs with the aid of a sinusoidal signal. Such a sinusoidal signal fills the energy blank in the gap between time where IOSs happen. This enables that the ridge detection approach, which is the necessary tool for mode retreival of SST-based methods, focuses on the assisted sinusoidal signal, rather than noise. Thus, the background noise in the gap is suppressed. As a result, SASST is capable of extracting wide-band IOSs in a strongly noisy environment. The effectiveness and advantages of the proposed algorithm are verified by both numerical simulations and real-world cases. Keywords: Sinusoidal-assisted, Time-frequency analysis, Synchrosqueezing, Biomedical © 2022, The Authors. All rights reserved.

关键词： Bioinformatics

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TSGN: Transaction Subgraph Networks Assisting Phishing Detection in Ethereum

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IEEE Transactions on Dependable and Secure Computing 2025年

作者： Wang, Jinhuan Chen, Pengtao Xu, Xinyao Wu, Jiajing Shen, Meng Xuan, Qi Yang, Xiaoniu Zhejiang University of Technology Institute of Cyberspace Security College of Information Engineering Hangzhou310023 China ZJUT Binjiang Institute of Artificial Intelligence Hangzhou310056 China Fudan University Adaptive Networks and Control Lab Department of Electronic Engineering School of Information Science and Technology Shanghai200433 China Sun Yat-sen University School of Computer Science and Engineering Guangzhou510006 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China Shenzhen518066 China National Key Laboratory of Electromagnetic Space Security Jiaxing314033 China

Due to the decentralized and public nature of the blockchain ecosystem, malicious activities on the Ethereum platform impose immeasurable losses on users. At the same time, the transparency of cryptocurrency transactions provides a unique opportunity to analyze illegal activities, such as phishing scams, from a network perspective. Most existing phishing scam detection methods focus primarily on analyzing account interaction networks, which limits their ability to uncover transaction behavior patterns embedded within transaction interactions. To address this, we construct the Transaction SubGraph Network (TSGN) by using transaction subgraphs as basic elements and further propose a novel framework for Ethereum phishing account detection. Specifically, we rebuild the graph structures via three well-designed mapping mechanisms, yielding TSGN and its two variants, i.e., Directed-TSGN and Temporal-TSGN, to obtain direction-aware and time-aware transfer flow features. By further incorporating the mapping strategy into transaction multidigraphs, we develop the Multiple-TSGN, which could preserve more transaction flow features while concurrently reducing the time consumption of modeling large-scale networks. TSGN models based on transaction subgraph interactions can capture complex higher-order dependencies, which lay beyond the reach of models that exclusively capture pairwise account interactions. As a general framework, our model can incorporate various feature extraction methods to improve the performance of phishing detection. Extensive experimental results on Ethereum datasets show that our method achieves superior performance in phishing detection, yielding 3.27%∼6.71% relative improvement over previous state-of-the-art. © 2004-2012 IEEE.

关键词： Phishing

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Graph-Enhanced Dual-Stream Feature Fusion with Pre-Trained Model for Acoustic Traffic Monitoring

Graph-Enhanced Dual-Stream Feature Fusion with Pre-Trained M...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shitong Fan Feiyang Xiao Wenbo Wang Shuhan Qi Qiaoxi Zhu Wenwu Wang Jian Guan Group of Intelligent Signal Processing Harbin Engineering University Harbin China Faculty of Computing Harbin Institute of Technology Harbin China School of Computer Science and Technology Harbin Institute of Technology Shenzhen China Acoustics Lab University of Technology Sydney Ultimo Australia Centre for Vision Speech and Signal Processing University of Surrey Guildford UK

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Microphone array techniques are widely used in sound source localization and smart city acoustic-based traffic monitoring, but these applications face significant challenges due to the scarcity of labeled real-world traffic audio data and the complexity and diversity of application scenarios. The DCASE Challenge’s Task 10 focuses on using multi-channel audio signals to count vehicles (cars or commercial vehicles) and identify their directions (left-to-right or vice versa). In this paper, we propose a graph-enhanced dual-stream feature fusion network (GEDF-Net) for acoustic traffic monitoring, which simultaneously considers vehicle type and direction to improve detection. We propose a graph-enhanced dual-stream feature fusion strategy which consists of a vehicle type feature extraction (VTFE) branch, a vehicle direction feature extraction (VDFE) branch, and a frame-level feature fusion module to combine the type and direction feature for enhanced performance. A pre-trained model (PANNs) is used in the VTFE branch to mitigate data scarcity and enhance the type features, followed by a graph attention mechanism to exploit temporal relationships and highlight important audio events within these features. The frame-level fusion of direction and type features enables fine-grained feature representation, resulting in better detection performance. Experiments demonstrate the effectiveness of our proposed method. GEDF-Net is our submission that achieved 1st place in the DCASE 2024 Challenge Task 10.

关键词： Location awareness Smart cities Signal processing Feature extraction Acoustics Data models Microphone arrays Speech processing Monitoring Faces

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A reinforcement learning and population-based discrete state transition algorithm for solving the multi-UAV task allocation problem with complex constraints

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Knowledge-Based Systems 2025年 325卷

作者： Xiaojun Zhou Runsong Xia Tingwen Huang School of Automation Central South University Changsha 410083 PR China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen 518055 PR China

In recent years, the application of unmanned aerial vehicle (UAV) technology in the military field has expanded significantly, making the cooperative task allocation problem for multiple UAVs a prominent research focus. This study aims to solve a mixed variable multi-objective UAV cooperative multi-task allocation problem (M-CMTAP) with complex constraints. A novel and effective mixed-variable encoding and feasible solution initialization method is adopted to address this complex problem. To increase the diversity of solutions in the discrete state transition algorithm (DSTA), the concept of population co-evolution is introduced into the DSTA, and reinforcement learning method is used to assist in evolution, leading to the proposal of a reinforcement learning and population-based discrete state transition algorithm (RL-PDSTA). Additionally, four new constraint-handling operators replace those in original DSTA, greatly improving both search efficiency and accuracy. The effectiveness and superiority of RL-PDSTA are validated through various military scenarios, and experimental results demonstrates the algorithm’s high efficiency in constraint handling and rapid iterative computation.

关键词： Discrete state transition algorithm Mixed variable complex constraints Multi-UAV task allocation Population cooperative evolution Reinforcement learning

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6DMA-Aided Hybrid Beamforming with Joint Antenna Position and Orientation Optimization

arXiv

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arXiv 2024年

作者： Zhang, Yichi Zhang, Yuchen Zhu, Lipeng Xiao, Sa Tang, Wanbin Eldar, Yonina C. Zhang, Rui National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu611731 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Kash Institute of Electronics and Information Industry Kash 844000 China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot7610001 Israel School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Guangdong Shenzhen518172 China

This paper studies a sub-connected six-dimensional movable antenna (6DMA)-aided multi-user communication system. In this system, each sub-array is connected to a dedicated radio frequency chain and collectively moves and rotates as a unit within specific local regions. The movement and rotation capabilities of 6DMAs enhance design flexibility, facilitating the capture of spatial variations for improved communication performance. To fully characterize the effect of antenna position and orientation on wireless channels between the base station (BS) and users, we develop a field-response-based 6DMA channel model to account for the antenna radiation pattern and polarization. We then maximize the sum rate of multiple users, by jointly optimizing the digital and unit-modulus analog beamformers given the transmit power budget as well as the positions and orientations of sub-arrays within given movable and rotatable ranges at the BS. Due to the highly coupled variables, the formulated optimization problem is non-convex and thus challenging to solve. We develop a fractional programming-aided alternating optimization framework that integrates the Lagrange multiplier method, manifold optimization, and gradient descent to solve the problem. Numerical results demonstrate that the proposed 6DMA-aided sub-connected structure achieves a substantial sum-rate improvement over various benchmark schemes with less flexibility in antenna movement and can even outperform fully-digital beamforming systems that employ antenna position or orientation adjustments only. The results also highlight the necessity of considering antenna polarization for optimally adjusting antenna orientation. Copyright © 2024, The Authors. All rights reserved.

关键词： Budget control

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Autonomous Vehicle Drift With a Soft Actor-critic Reinforcement Learning Agent 20

Autonomous Vehicle Drift With a Soft Actor-critic Reinforcem...

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20th IEEE Jubilee World Symposium on Applied Machine Intelligence and Informatics, SAMI 2022

作者： Hunor Toth, Szilard Janos Viharos, Zsolt Bardos, Adam Institute of Computer Science and Control Research Laboratory on Engineering Management Intelligence Intelligent Processes Research Group Budapest Hungary John von Neumann University Faculty of Economics Kecskemét Hungary Budapest University of Technology and Economics Department of Automotive Technologies Budapest Hungary

ISBN: (纸本)9781665497046

Self-driving vehicles have become a more and more important field in recent years. Supported by the techniques of Artificial Intelligence (AI), the current tendency of positive results in applications is making it a promising area to focus further research. Additionally, Reinforcement Learning (RL) is already proved to be an efficient approach for complex problems, e.g. robots, industrial systems and also games (like chess, Go), *** is a driving technique at handling limits where the driver intentionally oversteers, with loss of traction, while driving the vehicle through the entirety of a corner. It is a very challenging control task and often results in an accident when it occurs on public roads, consequently, the efficient control of this motion is especially important in the safety of autonomous *** paper reports novel research results whose main goal is to develop a self-driving agent for drift motion control based on vehicle simulation by Matlab/Simulink. Longitudinal and lateral velocity together with the yaw rate formed the state representation of the vehicle. The agent action space consists of two continuous actuator values: pedal ratio and roadwheel angle. The goal of the agent is twofold: first, it has to jump into a drifting state, second, it has to keep the vehicle in *** simulation results show that the proposed Soft Actor-Critic (SAC) RL agent is capable of learning to approach a pre-determined drift equilibrium from cornering and staying in this drift situation as well. For the training, the solution excluded using any kind of prior data, it only works with information gained from the simulation model, which is a remarkable difference from the actual state-of-the-art RL-based solutions. © 2022 IEEE.

关键词： Training Roads Simulation Reinforcement learning Mathematical models Data models Artificial intelligence

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