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SSRN 2023年

作者： Pan, Mei-Hong Xin, Hong-Yi Shen, Hong-Bin Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Jiaotong University Shanghai200240 China

Few-shot learning (FSL) as a data-scarce method, aims to recognize instances of unseen classes solely based on very few examples. However, the model can easily become overfitted due to the biased distribution formed with extremely limited training data. This paper presents a task specific data augmentation approach by transferring samples from base dataset to the novel tasks in an encoder-decoder paradigm, which guarantees generating semantically meaningful features. Specifically, the feature transfer process is carried out in semantic space. We further impose a compactness constraint to the generated features with the prototypes working as the reference points, which ensures the generated features distribute around the class centers. Moreover, we incorporate the cluster centers of the query set with the prototypes of the support set to reduce the bias of the class centers. With the supervision of the compactness loss, the model is encouraged to generate discriminative features with high inter-class dispersion and intra-class compactness. Extensive experiments show that our method outperforms the state-of-the-arts on four benchmarks, namely MiniImageNet, TieredImageNet, CUB and CIFAR-FS. © 2023, The Authors. All rights reserved.

关键词： Motion planning

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Research on Monocular Depth Estimation Method based on Multi-Level Attention and Feature Fusion

Research on Monocular Depth Estimation Method based on Multi...

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IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Zhongyu Wu Hua Huang Qishen Li Penghui Chen School of Information Engineering Nanchang Hangkong University Nanchang Jiangxi China Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Jiangxi China School of Software Nanchang Hangkong University Nanchang Jiangxi China

Monocular depth estimation is a fundamental task in computer vision and has drawn increasing attention. Recently, attention-based models and encoder-decoder architectures have led to great improvements in monocular depth estimation. Typically, most of the previous methods used repeated simple up-sampling operations during decoding, which may not make full use of the potential properties of the features extracted by the encoder, and there are problems of inaccurate prediction of the edge and depth maximum region. We propose an attention-based feature fusion module for encoder and decoder. We treat the monocular depth estimation as a pixel-level optimization problem, where the coarsest encoder feature is used to initialize the pixel-level optimization, which is then refined to higher resolution by the proposed attentional feature fusion (AFF). We formulate the prediction problem as ordinal regression over the bin centers that discretize the continuous depth range. It predicts a correspondingly different distribution of bins based on different pictures and we predict bins at the coarsest level using global pooling and MLP layers. In the NYUV2 dataset, the proposed architecture improving original model by 2.5.% and 1.1%, in terms of Log10 and Absolute relative error, respectively.

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Consensus-Based Distributed Algorithm for Gep

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SSRN 2022年

作者： Lv, Kexin He, Fan Huang, Xiaolin Yang, Jie Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University MOE Key Laboratory of System Control and Information Processing Shanghai200240 China

Generalized eigenvalue problem (GEP) plays a significant role in signal processing and machine learning. This paper proposes a consensus-based distributed algorithm for GEP in multi-agent systems, where data samples are distributively stored across agents. The distributed GEP is reformulated as a consensus optimization, but the presence of its quadratic inseparable constraint makes the considered problem more challenging. To deal with it, a sequential method is proposed combined with the alternating direction method of multipliers, which requires communication between couples of nodes. Theoretical analysis shows the proposed algorithm will converge to the set of stationary solutions. And the numerical experiments on synthetic and real-world datasets validate that the approximated solution is competitive to the ground truth. © 2022, The Authors. All rights reserved.

关键词： Multi agent systems

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Task-Oriented Multi-user Semantic Communication based on Deep Over-the-Air Computation

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IEEE Transactions on Vehicular Technology 2025年

作者： Wei, Shuangying Feng, Chunyan Guo, Caili Zhang, Biling Chen, Jiujiu Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China Nanchang Hangkong University Key Laboratory of Processing and Pattern Recognition of Jiangxi Province School of Information Engineering Nanchang330063 China

The presence of large-scale heterogeneous IoT devices and AI-based applications has brought significant transmission and computation pressure on the wireless communication system. In this paper, we propose a novel multi-user semantic communication framework based on deep over-the-air computation called SC-DAC to tackle this challenge. By integrating communication and computation through a deep over-the-air computation (AirComp) encoder, SC-DAC is able to utilize the superposition of multiple access channels, facilitating multi-user information fusion during transmission and eliminating the need for multi-user detection at the receiver. Further, to achieve the optimal task results, the semantic encoders, decoders, and AirComp encoder are jointly optimized, where stochastic gradient descent (SGD) algorithm and deep double-Q network (DDQN) are employed to optimize the encoder/decoder parameters. The simulation results demonstrate that as the number of users increased, the performance of the system remains relatively stable and shows potential in resource utilization. What's more, when applied to the AI-based tasks such as multi-user multimodal action recognition and semantic segmentation, SC-DAC enhances the accuracy of action recognition by 26% compared with traditional methods and by about 30%-50% compared with other multi-user semantic communication methods under conditions of low signal-to-noise ratio (SNR), while it enhances the accuracy of semantic segmentation by 0.22 to 0.32 compared to other methods © 1967-2012 IEEE.

关键词： Deep reinforcement learning

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Gait Planning and Motion Control Based on Vrep Simulation for Quadruped Robot

Gait Planning and Motion Control Based on Vrep Simulation fo...

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WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Linqi Zhou Zhihua Chen Jun Liu Zhi Liu Yumeng Chen Liting Zhang key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition and MOE Key Lab of Nondestructive Testing Technology Nanchang Hangkong University Nanchang China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot’s foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper.

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Research on the Strike Strategy of Quadcopter Unmanned Aerial Vehicles for Mobile Targets

Research on the Strike Strategy of Quadcopter Unmanned Aeria...

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WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Wencai Zhang Junjie Sun Yanying Li Shen Yan Ning Zhang Jiaqi Wang Zhihua Chen Mingran Pan Engineering Technicians of Norinco Group Liao Shen Industries Group CO.LTD Shenyang China Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition and MOE Key Lab of Nondestructive Testing Technology Nanchang Hangkong University Nanchang China

ISBN: (数字)9798331506100

ISBN: (纸本)9798331506117

This paper studies a strike path strategy for quadcopter drones targeting ground maneuvering targets. The strategy sets the strike path to two different strike speeds, which improves the stability and robustness of quadcopter drones while shortening strike time and increasing hit rates. Consider the attitude control of quadcopter unmanned aerial vehicles during motion, and verify the flight reliability of the mechanism through simulation experiments. Set different slope strike paths and obtain the optimal strike path through experiments, while proving the effectiveness of this strike strategy in engineering applications.

关键词： Attitude control Prototypes Autonomous aerial vehicles Stability analysis Robustness Robotics and automation Aircraft propulsion

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Thermal-Torsion Coupling Loading Analysis and Optimization of 3D PoP Assembly Solder Joints at Different Temperatures

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IEEE Transactions on Components, Packaging and Manufacturing Technology 2025年

作者： Gao, Chao Huang, Chunyue Liang, Yin Dian, Chen Lan, Jingyi Wang, Gui Guilin University of Electronic Technology School of Electrical and Mechanical Engineering Guilin541004 China Chengdu University Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province Chengdu610106 China Chengdu Aeronautic Vocational and Technical College Chengdu610021 China

A simulation analysis was conducted to investigate the stress distribution of Package-on-Package (PoP) assembly array solder joints subjected to thermal-torsional coupling loads, with the validity of the simulation confirmed through coupled loading stress-strain measurement experiments. The volume-weighted average method was employed to calculate the average equivalent stress (Δσ) of the critical solder joint danger element layer within the PoP assembly array, using Δσ as the evaluation benchmark. The impact and sensitivity of structural parameters on the thermal-torsional coupling stress of solder joints were examined. A structural parameter sensitivity model was developed to facilitate the stability and optimization analysis of the structural parameter intervals. The results indicate that solder joints in the lower array of the PoP assembly experience higher thermal-torsional coupling stress, with the peak internal stress occurring at the interface between the solder joint and the copper pad. The variation in thermal-torsional coupling stress of the array solder joints is more pronounced in the low-temperature region compared to the high-temperature region, with maximum stress occurring at -55°C and minimum stress observed at 125°C. Within the structural parameter range, the Δσ value of the critical solder joint shows a negative correlation with solder joint height, solder joint diameter, and substrate thickness, and a positive correlation with PCB thickness. The sensitivity to structural parameters follows the order: solder joint diameter, solder joint height, PCB thickness, and substrate thickness. Finally, the optimal range of structural parameters was determined, and the stability of this range was assessed. © 2011-2012 IEEE.

关键词： Sensitivity analysis

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New Traveling Wave Solutions and Dynamic Behavior Analysis of the Nonlinear Rangwala-Rao Model

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SSRN 2023年

作者： Peng, Chen Li, Zhao College of Computer Science Chengdu University Chengdu610106 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province Chengdu University 610106 China

This work investigates the nonlinear Rangwala-Rao equation, which stems from the mixed derivative nonlinear Schrödinger equation. For retrieving new exact solutions to the equation, the complete discriminant system for polynomial method is employed. In results, some novel traveling wave solutions, including solitary wave solutions, triangular function solutions, periodic solutions and Jacobi elliptic function solutions are obtained and demonstrated through numerical simulations. The bifurcations of phase portraits of the traveling wave solutions are depicted to reveal the dynamic behavior of the Rangwala-Rao equation using the qualitative theory of dynamical systems. Furthermore, considering external perturbation, the chaotic motions of the perturbed Rangwala-Rao equation are investigated. © 2023, The Authors. All rights reserved.

关键词： Dynamical systems

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Dynamic Effects on Traveling Wave Solutions of the Space-Fractional Long-Short-Wave Interaction System with Multiplicative White Noise

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SSRN 2023年

In this paper, the stochastic space-fractional long-short-wave interaction system (SF-LSWIS) with multiplicative white noise is considered. The stochastic exact solutions including triangular function solutions, hyperbolic function solutions as well as Jacobian elliptic function solutions are obtained via complete discriminant system for polynomial method. For this purpose, the traveling wave transformation is applied to carry out the ordinary differential equation of this model, which is also converted to a dynamical system. Thereafter, Qualitative behavior, bifurcation of the phase portraits and chaotic behaviors of the system are studied. Furthermore, the 3D surface, graphs of contour plots and level curves of some exact solutions are depicted by choosing proper parameter values. The influence and effect of fractional derivative and the noise strength on the solutions are also studied. © 2023, The Authors. All rights reserved.

关键词： Hyperbolic functions

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Detection of Venous Thromboembolism Using Recurrent Neural Networks with Time-Series Data 24

Detection of Venous Thromboembolism Using Recurrent Neural N...

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3rd Asia Conference on Algorithms, Computing and Machine Learning, CACML 2024

作者： Xu, Can Huang, Yaqin Xiang, Xinni Lei, Haike Yang, Jie Shanghai Jiao Tong University Shanghai China Chongqing University Cancer Hospital Chongqing China West China Hospital Sichuan University Chengdu China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition China Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment China West China School of Medicine China Chongqing Cancer Multi-omics Big Data Application Engineering Research Center China

ISBN: (纸本)9798400716416

Machine Learning (ML) has been widely applied to medical science for decades. As common knowledge, the progress of many diseases is often chronic and dynamic. Longitudinal data, or time-series data, has better descriptions of certain diseases, as it naturally captures the dynamic over time. Venous thromboembolism (VTE), as a regular complication of cancer tumour treatments, has been emphasized in many studies. Recent research has shown that ML algorithms incredibly contribute to VTE risk estimation and prediction. However, existing methods rarely consider the dynamic changes during the development of VTE, and often make decisions based on time-point data, such as the latest blood test results of patients. In this paper, we propose a VTE detection model that takes advantage of capturing dynamic information using time-series data. The model consists of a Recurrent Neural Network (RNN) based framework with time embedding and Attention mechanism to encode longitudinal features of patients. We test our proposed model on a real-world dataset that contains multiple times of blood test results of patients together with other clinical features. The network is compared with several commonly used ML models in previous VTE studies. The results show that our model outperforms all baseline models, and achieved a state-of-art performance with 80.0% accuracy and 0.881 AUC. © 2024 ACM.

关键词： Risk assessment

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