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Specificity-preserving RGB-D saliency detection

Computational Visual Media 2023年第2期9卷 297-317页

作者： Tao Zhou Deng-Ping Fan Geng Chen Yi Zhou Huazhu Fu School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Key Laboratory of System Control and Information Processing Ministry of EducationShanghaiChina Computer Vision Lab ETH Z¨urichZ¨urichSwitzerland School of Computer Science and Engineering Northwestern Polytechnical UniversityXi’anChina School of Computer Science and Engineering Southeast UniversityNanjingChina Inception Institute of Artificial Intelligence Abu DhabiUnited Arab Emirates

Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few methods explicitly consider how to preserve modality-specific *** this study,we propose a novel framework,the specificity-preserving network(SPNet),which improves SOD performance by exploring both the shared information and modality-specific ***,we use two modality-specific networks and a shared learning network to generate individual and shared saliency prediction *** effectively fuse cross-modal features in the shared learning network,we propose a cross-enhanced integration module(CIM)and propagate the fused feature to the next layer to integrate cross-level ***,to capture rich complementary multi-modal information to boost SOD performance,we use a multi-modal feature aggregation(MFA)module to integrate the modalityspecific features from each individual decoder into the shared *** using skip connections between encoder and decoder layers,hierarchical features can be fully *** experiments demonstrate that our SPNet outperforms cutting-edge approaches on six popular RGB-D SOD and three camouflaged object detection *** project is publicly available at https://***/taozh2017/SPNet.

关键词： salient object detection(SOD) RGB-D cross-enhanced integration module(CIM) multi-modal feature aggregation(MFA)

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DDoS Attack Detection for Cloud control System Based on BiLSTM Algorithm

DDoS Attack Detection for Cloud Control System Based on BiLS...

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2022 Chinese Automation Congress, CAC 2022

作者： Xu, Shengliang Zheng, Song Fuzhou University College of Electrical Engineering and Automation Fuzhou350116 China Fuzhou University of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing Fuzhou350116 China

ISBN: (纸本)9781665465335

The huge advantages of cloud computing technology and the bottlenecks in the development of traditional network control systems have prompted the birth of cloud control systems to address the shortcomings of traditional network control systems in terms of bandwidth and performance. However, the information security issues faced by cloud control systems are more complex, and distributed denial-of-service (DDoS) attacks are a typical class of attacks that may lead to problems such as latency in cloud control systems and seriously affect the performance of cloud control systems. In this paper, we build a single-capacity water tank cloud control semi-physical simulation system with heterogeneous controllers and propose a DDoS attack detection method for cloud control systems based on bidirectional long short-term memory neural network (BiLSTM), study the impact of DDoS attacks on cloud control systems. The experimental results show that the BiLSTM algorithm can effectively detect the DDoS attack on the cloud control system. © 2022 IEEE.

关键词： Denial-of-service attack

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High-efficiency Brillouin lasing in a planar GeSbS spiral-ring resonator

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Chinese Optics Letters 2024年第7期22卷 71-76页

作者： Jingcui Song Yuhang Wei Chunxu Wang Shuixian Yang Yan Li Tianhua Feng Xiaojie Guo Zhaohui Li Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems and School of Electronics and Information Technology Sun Yat-sen UniversityGuangzhou 510006China Peng Cheng Laboratory Shenzhen 518000China Department of Electronic Engineering College of Information Science and TechnologyJinan UniversityGuangzhou 510632China Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications Institute of Photonics TechnologyJinan UniversityGuangzhou 510632China College of Physics and Optoelectronic Engineering Jinan UniversityGuangzhou 510632China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519000China

Stimulated Brillouin scattering in planar integrated circuits promises to realize compact and highly coherent *** we report efficient Brillouin lasing at telecommunication wavelength from a planar Ge_(25)Sb_(10)S_(65) chalcogenide(ChG)resonator with a high quality factor above 106.A low lasing threshold of 24.8 mW is achieved with a slope efficiency of 8.3%.An 8-kHz linewidth is measured for 1.56-mW on-chip output *** work offers a good opportunity to enrich the versatility and functionality of the ChG photonics on account of their intrinsic advantages of low loss,high third-order nonlinearity,and potential capacity for wafer-scale fabrication.

关键词： Brillouin lasing chalcogenide photonics planar integrated circuit high-Q resonator

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Distributionally Robust control Synthesis for Stochastic systems with Safety and Reach-Avoid Specifications

arXiv

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arXiv 2025年

作者： Chen, Yu Li, Yuda Li, Shaoyuan Yin, Xiang Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

We investigate the problem of synthesizing distributionally robust control policies for stochastic systems under safety and reach-avoid specifications. Using a game-theoretical framework, we consider the setting where the probability distribution of the disturbance at each time step is selected from an ambiguity set defined by the Wasserstein distance. The goal is to synthesize a distributionally robust control policy that ensures the satisfaction probability exceeds a specified threshold under any distribution within the ambiguity set. First, for both safety and reach-avoid specifications, we establish the existence of optimal policies by leveraging the dynamic programming principles. Then we demonstrate how the associated optimization problem can be efficiently solved using the dual representation of Wasserstein distributionally robust optimization. Furthermore, for safety specifications in particular, we introduce a novel concept of distributionally robust control barrier certificates and show how these enable the efficient synthesis of controllers through sum-of-squares programming techniques. Finally, our experimental results reveal that incorporating distributional robustness during the synthesis phase significantly improves the satisfaction probability during online execution, even with limited statistical knowledge of the disturbance distribution. Copyright © 2025, The Authors. All rights reserved.

关键词： Stochastic systems

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Rolling Bearing Fault Diagnosis Method Based on Wavelet Time–Frequency Map and Improved ConvNext 1

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UNIfied Conference of International Workshop on Defence Applications of Multi-Agent systems, DAMAS 2023, International Conference on Maintenance Engineering, IncoME-V 2023, International conference on the Efficiency and Performance Engineering Network, TEPEN 2023

作者： Qin, Feifan Zhang, Chao Wang, Jianguo Zhao, Wentao Li, Jianjun Liu, Tongtong College of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014010 China Inner Mongolia Key Laboratory for Intelligent Diagnosis and Control of Electromechanical Systems Baotou014010 China College of Information Engineering Inner Mongolia University of Science and Technology Baotou014010 China

ISBN: (数字)9783031494215

ISBN: (纸本)9783031494208

The purpose of this article is to address the issue of traditional fault diagnosis methods for rolling bearings, which are unable to accurately diagnose the fault signals of non-linear and non-stationary rolling bearings. To achieve this goal, this article proposes a rolling bearing fault diagnosis method based on wavelet time–frequency maps and an improved ConvNext model. This method first leverages the advantages of wavelet time–frequency analysis to transform the original signal into a two-dimensional wavelet time–frequency map. Subsequently, a new generation of convolutional neural networks, ConvNext, is utilized as the foundational network for rolling bearing fault diagnosis models. The network is enhanced by introducing lightweight attention modules, such as the Convolutional Block Attention Module (CBAM) and the Efficient Channel Attention Network (ECA), to improve the Block modules in the basic network. The wavelet time–frequency map is then used as a feature map input to the improved ConvNext network for training, aiming to achieve rolling bearing fault diagnosis recognition. Finally, experimental results demonstrate that the proposed method exhibits a high level of fault recognition accuracy and stability in laboratory data. It also demonstrates a certain degree of robustness, offering a new solution for rolling bearing fault diagnosis. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Failure analysis

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An Efficient Asynchronous Circuits Design Flow with Backward Delay Propagation Constraint

An Efficient Asynchronous Circuits Design Flow with Backward...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Lingfeng Zhou Shanlin Xiao Huiyao Wang Jinghai Wang Zeyang Xu Bohan Wang Zhiyi Yu School of Microelectronics Science and Technology Sun Yat-sen University China Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems China

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

Asynchronous circuits have recently become more popular in Internet of Things (IoT) and neural network chips because of their potential low power consumption. However, due to the lack of Electronic Design Automation (EDA) tools, the asynchronous circuits design efficiency remains low and faces challenges in large-scale applications. This paper proposes a new asynchronous circuits design flow using traditional EDA tools, and applies a new backward delay propagation constraint (BDPC) method. In this method, control paths and data paths are tightly coupled and analyzed together to improve the accuracy of static timing analysis. Compared to previous works, the proposed design flow and constraint method offer significant advantages in terms of accuracy and efficiency. To verify this flow, an asynchronous RISC-V processor was implemented on TSMC 65nm process. Compared to synchronous version, asynchronous processor achieves a power optimization of 17.4 % while main-taining the same speed and area.

关键词： Electric potential Power demand Design automation Neural networks Delays Internet of Things Optimization

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Resource Allocation and Task Offloading Strategy Base on Hybrid Simulated Annealing-Binary Particle Swarm Optimization in Cloud-Edge Collaborative System 5

Resource Allocation and Task Offloading Strategy Base on Hyb...

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5th IEEE Advanced information Management, Communicates, Electronic and Automation control Conference, IMCEC 2022

作者： Chen, Xue Zheng, Song College of Electrical Engineering and Automation Fuzhou University Fuzhou350116 China Fuzhou University of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing Fuzhou350116 China

ISBN: (纸本)9781665479677

Taking the latency, energy consumption and computing resource cost into consideration comprehensively, we construct a single-cell, multi-user cloud-edge collaborative system model and decompose the optimization problem of task offloading and resource allocation aiming at minimizing the total user overhead into three sub-problems: computing resource allocation, uplink power allocation and task offloading. Computing resource and uplink power allocation are optimized by using convex optimization technique and bisection method respectively. To optimize task offloading, we propose a simulated annealing-binary particle swarm optimization algorithm(SA-BPSO). Simulation results show that SA-BPSO can better reduce the total user overhead compared with the other three schemes and ensure user quality of service quality. © 2022 IEEE.

关键词： Resource allocation

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Continuous-variable Quantum key Distribution Access Network

Continuous-variable Quantum Key Distribution Access Network

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Tao Wang Yuehan Xu Lang Li Xu Liu Zicong Tan Peng Huang Guihua Zeng State Key Laboratory of Advanced Optical Communication Systems and Networks Center of Quantum Sensing and Information Processing Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

Quantum key distribution (QKD) networks are crucial for the development of quantum networks and the early stages of the quantum internet, enabling unconditional secure key distribution and guaranteeing data security. However, current QKD networks are still limited in their structure, and are hard to achieve super multi-user access due to high system costs associated with the original point-to-point QKD system. In this paper, we introduce two cost-effective continuous-variable QKD (CV-QKD) access network schemes. The first one is a round-trip multi-band CV-QKD access network. Specifically, the frequency division multiplexing (FDM) technology is used to support multi-user access, and the round-trip optical architecture is adopted to realize low cost. As a result of the encoding properties of CV-QKD, different users can utilize the quadrature components in various frequency bands to transmit key information. The proposed network theoretically supports hundreds of users and can be easily expanded using simple equipment. The second one is a CV-QKD access network based on directed detection. With the help of the Kramers-Kronig relation, the receiver at the optical network unit can obtain the quadrature components just using a photodetector. Besides, it can also solve the practical issues in the plug-and-play structure. Compared with a quantum access network based on the point-to-point QKD system, these two schemes can provide cost-effective solutions for the subsequent large-scale verification and implementation of quantum access networks.

关键词： Costs Optical network units Photodetectors Optical receivers Encoding Quantum key distribution Frequency division multiplexing

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Detecting Defects of Wooden Boards by Improved YOLOv4-tiny Algorithm 17th

Detecting Defects of Wooden Boards by Improved YOLOv4-tiny A...

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17th Chinese Intelligent systems Conference, CISC 2021

作者： Qiu, Yang Ai, Zhijie Lin, Ye Xu, Zhezhuang Liu, Xinxiang College of Electrical Engineering and Automation Fuzhou University Fuzhou350000 China Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9789811663192

Wooden boards are widely used as raw materials for furniture. Detecting defects on the wooden is significant to improve the quality of products. In this paper, we propose an improved YOLOv4-tiny target detection algorithm with feature extraction and utilization tailored for wood defect recognition. The proposed algorithm replace the residual network of the original algorithm with the Res2Net network to enhance the feature extraction ability, and increase the different scales to improve the prediction accuracy. A testbed is deployed to collect the images of wooden boards, and the performance of the proposed algorithm is evaluated on the testbed. Compared with the original YOLOv4-tiny algorithm, the mean average precision for detecting the three types of defects deadknot, insectpest and crack was 80.06% which was an increase of 5%. Compared with other methods of wood defect detection, the proposed algorithm is more accurate and faster. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Testbeds

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Quality Prediction of Injection Molding Process Using CNN and Parallel-Cascade LSTMs 43

Quality Prediction of Injection Molding Process Using CNN an...

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43rd Chinese control Conference, CCC 2024

作者： Zhang, Yibo Li, Dewei Zhou, Yuanqiang Gao, Furong Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai201100 China Tongji University College of Electronic and Information Engineering Shanghai201804 China Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong The Guangzhou Hkust Fok Ying Tung Research Institute Department of Chemical and Biological Engineering Guangzhou511458 China

ISBN: (纸本)9789887581581

Quality prediction of plastic products has always been an important research topic in the injection molding production process. However, existing quality prediction methods struggle to handle both high-frequency data and statistical data generated during the injection molding production process. This paper introduces a novel quality prediction model for injection molding production, utilizing a combination of Convolutional Neural Networks (CNN) and Parallel-Cascade Long Short-Term Memory (PCLSTM) networks. The PCLSTM network is designed to handle the complexities of high-frequency data in injection molding, overcoming the limitations of traditional LSTM methods in processing long sequence data. By segmenting data into stages and utilizing a cascade mechanism, the PCLSTM architecture efficiently captures important temporal dynamics. Additionally, the CNN network is designed to extract statistical data features. The quality prediction results are obtained by fusing two types of data features and then passing them through a fully connected network. Experimental results on real production datasets show that the CNN-PCLSTM model outperforms existing models in prediction accuracy and training convergence speed. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Convolutional neural networks

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