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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Yin, Qingshan Zhao, Qiaochu Jia, Huijie Gao, Yan Feng, Luoluo Li, Chaoming Cheng, Yao Lin, Bin Shandong New Generation Information Industrial Technology Research Institute Artificial Intelligence Research and Development Center Jinan China Dalian Maritime University Information Science and Technology College DaLian China

ISBN: (纸本)9798350345384

Gesture recognition and hand pose estimation are two important tasks in the field of computer vision;however, in hand-object interaction scenarios, it is still challenging to implement gesture recognition and hand pose estimation using monocular RGB images since the hands are often obscured by objects. Most current studies treat these two problems as separate tasks. This paper proposes a multi-task network that combines gesture recognition and hand pose estimation tasks in a single network to solve this issue. The network uses a novel hand-object feature interaction module to improve the accuracy of gesture recognition and pose estimation by reasoning about the context between hand and object features through Transformer that encodes hand features and object features in different manners. In addition, to improve the performance of the multi-task network, we use a collaborative learning method that combines the output features of different tasks to promote each other, thus further improving the overall performance. Our model achieves high accuracy and performance for both gesture recognition and gesture pose estimation tasks on both the FPHA and HO-3D datasets, demonstrating the effectiveness and feasibility of the method. © 2023 IEEE.

关键词： Gesture recognition

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Graphene/F_(16)CuPc synaptic transistor for the emulation of multiplexed neurotransmission

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Journal of Semiconductors 2025年第1期46卷 215-223页

作者： Zhipeng Xu Yao Ni Mingxin Sun Yiming Yuan Ning Wu Wentao Xu Institute of Photoelectronic Thin Film Devices and Technology Key Laboratory of Photoelectronic Thin Film Devices and Technology of TianjinCollege of Electronic Information and Optical EngineeringEngineering Research Center of Thin Film Photoelectronic Technology of Ministry of EducationNankai UniversityTianjin 300350China Shenzhen Research Institute of Nankai University Shenzhen 518000China Smart Sensing Interdisciplinary Science Center Nankai UniversityTianjin 300350China School of Integrated Circuits Guangdong University of TechnologyGuangzhou 510006China

We demonstrate a bipolar graphene/F_(16)CuPc synaptic transistor(GFST)with matched p-type and n-type bipolar properties,which emulates multiplexed neurotransmission of the release of two excitatory neurotransmitters in graphene and F_(16)CuPc channels,*** process facilitates fast-switching plasticity by altering charge carriers in the separated *** complementary neural network for image recognition of Fashion-MNIST dataset was constructed using the matched relative amplitude and plasticity properties of the GFST dominated by holes or electrons to improve the weight regulation and recognition accuracy,achieving a pattern recognition accuracy of 83.23%.These results provide new insights to the construction of future neuromorphic systems.

关键词： synaptic transistor dual excitatory channels fast-switching plasticity multiplexed neurotransmission

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research on cycle life prediction model of electronic bonding structure based on Anand equation

Research on cycle life prediction model of electronic bondin...

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2024 International Conference on Advanced Control Systems and Automation Technologies, ACSAT 2024

作者： Zhang, Guoyong The 10th Research Institute of China Electronics Technology Corporation Chengdu610036 China Sichuan Engineering Technology Research Center for Electricity Interconnect of Electronic Information Equipment Chengdu610036 China

ISBN: (纸本)9798331541668

In the field of electronic information equipment, the package reliability of power semiconductor devices plays a key role in the use of products. However, the traditional optimized design faces the disadvantages of long research and development cycle, high development cost, etc., and there is an urgent need to accelerate the transformation of digital research and development model. Therefore, in this work we developed a temperature life prediction model for the connection interface of power semiconductor devices based on Anand's equation and used it as a design objective to optimize the size of the substrate and the geometry of the microstructure. The model can realize multi-professional collaborative linkage, significantly improve design efficiency, comprehensively reduce development costs, and can realize a large number of complex simulation calculations. © 2024 IEEE.

关键词： bonding component digital model finite element simulation optimal design

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OdCFU-Net for Brain Tumor Segmentation Based on MRI

OdCFU-Net for Brain Tumor Segmentation Based on MRI

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2024 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2024

作者： Wu, Shang Yang, Sijing Li, Boyue Yin, Shimin Zhu, Jianming Li, Shiyong Chen, Zhencheng Guilin University of Electronic Science and Technology School of Computer and Information Security China School of Electronic Engineering and Automation Guilin University of Electronic Technology Guilin China Key Laboratory of Biomedical Sensors and Intelligent Instruments Guangxi Colleges and Universities Guilin China Guangxi Engineering Technology Research Center of Human-Physiological Information Noninvasive Detection Guilin China School of Computer and Information Security Guilin University of Electronic Science and Technology China

ISBN: (纸本)9798350322996

In the field of medical image analysis, the accurate segmentation of brain tumors plays a crucial role in the diagnosis and treatment of brain-related diseases. This study aims to address key challenges in this domain, with a particular focus on improving feature extraction, information integration, and model generalization capabilities. By concurrently introducing multi-dimensional attention mechanisms in convolutional operations, a method has been developed to dynamically generate convolution kernels in spatial, input channel, and output channel dimensions. This approach optimizes the limitations of traditional static convolutional kernels, maintaining high-performance efficiency while reducing the model's parameter count. To overcome the deficiencies of traditional convolutional networks in capturing global information, channel and spatial attention mechanisms have been integrated between convolutional layers. This enhances adaptability and global information retrieval capabilities, allowing the model to dynamically adjust the weight of feature maps based on different task requirements. Leveraging the advantages of Vision Transformer in handling global information and addressing its limitations in capturing details and training on small datasets, the algorithm aligns and learns feature representations effectively by incorporating channel attention and normalizing attention weights within its multi-head attention. When applied to the BraTs2021 multi-modal brain tumor image database, the proposed algorithm accurately delineates brain tumor regions, demonstrating excellent performance. © 2024 IEEE.

关键词： Semantic Segmentation

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Definability of Relations by Semigroups of Isotone Transformations

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Journal of Applied and Industrial Mathematics 2024年第1期18卷 60-69页

作者： Klyushin, A.A. Kozhukhov, I.B. Manilov, D. Yu. Reshetnikov, A.V. Cadence Design Systems CorkT23 KW81 Ireland National Research University of Electronic Technology Moscow124498 Russia Lomonosov Moscow State University Moscow119991 Russia ELVEES Research and Development Center Moscow Zelenograd1244660 Russia

Abstract: In 1961, L.M. Gluskin proved that a given set with an arbitrary nontrivial quasiorder is determined up to isomorphism or anti-isomorphism by the semigroup of all isotone transformations of, i.e., the transformations of preserving. Subsequently, L.M. Popova proved a similar statement for the semigroup of all partial isotone transformations of;here the relation does not have to be a quasiorder but can be an arbitrary nontrivial reflexiveor antireflexive binary relation on the set. In the present paper, under the same constraints on the relation, we prove that the semigroup of all isotone binary relations (set-valued mappings) of determines up to an isomorphism or anti-isomorphism as well. In addition, for each ofthe conditions,, and, we enumerate all-ary relations satisfying the given condition. © Pleiades Publishing, Ltd. 2024.

关键词： Set theory

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Intelligent recognition and information extraction of radar complex jamming based on time-frequency features

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Journal of Systems Engineering and electronics 2024年第5期35卷 1148-1166页

作者： PENG Ruihui WU Xingrui WANG Guohong SUN Dianxing YANG Zhong LI Hongwen College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China Qingdao Innovation and Development Center Harbin Engineering UniversityQingdao 266000China Information Fusion Research Institute Naval Aeronautical UniversityYantai 264001China National Key Laboratory of Science and Technology on Vessel Integrated Power System Naval University of EngineeringWuhan 430033China

In modern war,radar countermeasure is becoming increasingly fierce,and the enemy jamming time and pattern are changing more *** is challenging for the radar to efficiently identify jamming and obtain precise parameter information,particularly in low signal-to-noise ratio(SNR)*** this paper,an approach to intelligent recognition and complex jamming parameter estimate based on joint time-frequency distribution features is proposed to address this challenging ***,a joint algorithm based on YOLOv5 convolutional neural networks(CNNs)is proposed,which is used to achieve the jamming signal classification and preliminary parameter ***,an accurate jamming key parameters estimation algorithm is constructed by comprehensively utilizing chi-square statistical test,feature region search,position regression,spectrum interpolation,etc.,which realizes the accurate estimation of jamming carrier frequency,relative delay,Doppler frequency shift,and other ***,the approach has improved performance for complex jamming recognition and parameter estimation under low SNR,and the recognition rate can reach 98%under−15 dB SNR,according to simulation and real data verification results.

关键词： complex jamming recognition time frequency feature convolutional neural network(CNN) parameter estimation

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A self-driving solution for resource-constrained autonomous vehicles in parked areas

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High-Confidence Computing 2024年第1期4卷 32-42页

作者： Jin Qian Liang Zhang Qiwei Huang Xinyi Liu Xiaoshuang Xing Xuehan Li College of Information Engineering Taizhou UniversityTaizhou 225300China Engineering Research Center of Integration and Application of Digital Learning Technology Ministry of EducationBeijing 100039China School of Computer Science and Engineering Changshu Institute of TechnologyChangshu 215500China The School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China

Autonomous vehicles in industrial parks can provide intelligent,efficient,and environmentally friendly transportation services,making them crucial tools for solving internal transportation *** the characteristics of industrial park scenarios and limited resources,designing and implementing autonomous driving solutions for autonomous vehicles in these areas has become a research *** paper proposes an efficient autonomous driving solution based on path planning,target recognition,and driving decision-making as its core *** designs for path planning,lane positioning,driving decision-making,and anti-collision algorithms are *** analysis and experimental validation of the proposed solution demonstrate its effectiveness in meeting the autonomous driving needs within resource-constrained environments in industrial *** solution provides important references for enhancing the performance of autonomous vehicles in these areas.

关键词： Autonomous vehicles Path planning Target recognition Driving decision-making Self-driving

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Structure and luminescence study of Gd3+ sensitized Sr2YF7: Eu3+: A novel red luminescent phosphor for high-performance white light diodes and fingerprints

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Ceramics International 2025年第14期51卷 19267-19281页

作者： Yan, Miao Pei, Xiaoqing Liu, Yifan Fan, Lin Jiang, Tao Mi, Zibo Liu, Lina Li, Chun Lin, Hai Li, Shasha Yang, Weiling Zeng, Fanming Su, Zhongmin School of Materials Science and Engineering Changchun University of Science and Technology Changchun130022 China Engineering Research Center of Optoelectronic Functional Materials Ministry of Education Changchun130022 China Jilin University Changchun130012 China Jilin Technology College of Electronic Information Jilin 132021 China

Due to the lack of effective strategies to simultaneously address the two challenging issues of poor luminous efficiency and low thermal stability, the development and large-scale application of solid-state lighting technology are unable to overcome bottlenecks. Therefore, Eu3+ red phosphors were synthesized using the hydrothermal method, with the introduction of Gd3+ to replace Y3+ in the host lattice resulting in a significant improvement in luminescence performance. The luminous intensity of Sr2YF7: 0.1Eu3+, 0.06Gd3+ phosphor at 591 nm increased by 5.50 times. This enhancement can be attributed to the improved local crystal field environment of the doped phosphor. The quantum efficiency of Sr2YF7: 0.1Eu3+ and Sr2YF7: 0.1Eu3+, 0.06Gd3+ phosphors reached 57.88 % and 84.32 % respectively, with the increase in electron traps with a quantum confinement structure after the replacement of Y3+ by Gd3+ contributing to this improvement. Both Eu3+ doped and Eu3+/Gd3+ co-doped phosphors demonstrated thermal stability as high as 90.58 % and 94.59 %, showcasing excellent performance in this aspect. The calculation of the Debye temperature ΘD further supported the exceptional thermal stability of the phosphor. Furthermore, the synthesized phosphor exhibited excellent moisture resistance. The study explored the application of these phosphors in WLEDs and fingerprint detection, showing promising performance. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Gadolinium compounds

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Feature Weighting and Fusion for Few-shot Object Detection in Remote Sensing Images 4

Feature Weighting and Fusion for Few-shot Object Detection i...

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Deng, Lianyin Song, Yunkai Xie, Honggang Ye, Yunyao Yuan, Zi Xiao, Jinsheng China Academy of Space Technology Research Center Beijing100080 China Wuhan University School of Electronic Information Wuhan430072 China Hubei University of Technology School of Electrical and Electronic Engineering Wuhan430068 China

ISBN: (纸本)9798350349252

Few-shot object detection (FSOD) trains detectors to recognize new objects using very limited data, making it a challenging task in scenarios with scarce labeled examples. In this paper, a small-sample remote sensing target detection method with feature weighting and fusion is proposed by using the meta-learning method. Firstly, the bottleneck structural feature learning module C3 is embedded in the meta-feature extraction network to increase the network depth and receptive field. Secondly, the path aggregation network is used for meta-feature fusion, which effectively improves the perception ability of the network for multi-scale remote sensing targets. Finally, the lightweight convolutional neural network is used to learn the prototype vector to weight the meta-features. The existing knowledge of the model is used to quickly fine-tune the model to adapt to the detection of new types of targets while lightening the model. The experimental results show that the average detection accuracy of the new class of objects reaches 68% and 33% under the 10-shot on the NWPU VHR-10 and DIOR datasets. The visualization results show that the proposed method has a better effect on the detection of small-sample remote sensing targets. © 2024 IEEE.

关键词： Convolutional neural networks

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Improving ECAPA-TDNN Performance with Coordinate Attention

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Journal of Shanghai Jiaotong University (Science) 2024年 1-7页

作者： Liu, Shuanghong Song, Zhida He, Liang School of Computer Science and Technology Xinjiang University Urumqi830017 China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi830017 China Department of Electronic Engineering and Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China

The current mainstream networks, such as squeeze and excitation residual neural network (SE-ResNet) and emphasized channel attention, propagation and aggregation based time delay neural network (ECAPA-TDNN), enhance the capability of speaker embedding extractors to extract more discriminative speaker embeddings by incorporating squeeze and excitation (SE) attention within the convolutional blocks. However, the SE attention focuses solely on encoding inter-channel information, overlooking the importance of spatial positional information and time-frequency information, which are crucial for the model’s performance. In this paper, we first experimentally compare the effectiveness of several mainstream attention mechanisms in the computer vision domain for the ECAPA-TDNN model. Next, we focus on the substantial improvements that coordinate attention (CA) brings to the ECAPA-TDNN model. The introduction of CA can help the model embed time-frequency information into the channel representation. Even without using AS-Norm, our proposed model achieves relative reductions of about 5.3% equal error rate (EER) and 5.5% minimum detection cost function (minDCF) on both the Voxceleb-O and Voxceleb-H test sets compared to the ECAPA-TDNN baseline model. In addition, the EER is relatively reduced by 9.46% on the CN-Celeb1 test set. This result strongly demonstrates that the CA module can effectively improve the generalization ability of the ECAPA-TDNN model. © Shanghai Jiao Tong University 2024.

关键词： Neural network models

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