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Expression Recognition Method Based on Convolutional Neural Network and Capsule Neural Network

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Computers, Materials & Continua 2024年第4期79卷 1659-1677页

作者： Zhanfeng Wang Lisha Yao school of Computer Science and artificial intelligence Chaohu UniversityHefei238000China school of Big Data and artificial intelligence Anhui Xinhua UniversityHefei230088China

Convolutional neural networks struggle to accurately handle changes in angles and twists in the direction of images,which affects their ability to recognize patterns based on internal feature levels. In contrast, CapsNet overcomesthese limitations by vectorizing information through increased directionality and magnitude, ensuring that spatialinformation is not overlooked. Therefore, this study proposes a novel expression recognition technique calledCAPSULE-VGG, which combines the strengths of CapsNet and convolutional neural networks. By refining andintegrating features extracted by a convolutional neural network before introducing theminto CapsNet, ourmodelenhances facial recognition capabilities. Compared to traditional neural network models, our approach offersfaster training pace, improved convergence speed, and higher accuracy rates approaching stability. Experimentalresults demonstrate that our method achieves recognition rates of 74.14% for the FER2013 expression dataset and99.85% for the CK+ expression dataset. By contrasting these findings with those obtained using conventionalexpression recognition techniques and incorporating CapsNet’s advantages, we effectively address issues associatedwith convolutional neural networks while increasing expression identification accuracy.

关键词： Expression recognition capsule neural network convolutional neural network

No Reference Image Sharpness Assessment Based on Global Color Difference Variation

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Chinese Journal of Electronics 2024年第1期33卷 293-302页

作者： Chenyang SHI Yandan LIN school of artificial intelligence Anhui Polytechnic University school of Mechanical Engineering Anhui Polytechnic University Department of Light Sources and Illuminating Engineering Fudan University Academy for Engineering & Technology Fudan University

Image quality assessment(IQA) model is designed to measure the image quality in consistent with subjective ratings by computational models. In this research, a valid no reference IQA(NR-IQA) model for color image sharpness assessment is proposed based on local color difference map in a color space. In the proposed model, the absolute color difference variation and relative color difference variation are combined to evaluate sharpness in YIQ color space(a color coordinate system for the development of the United States color television system). The difference between sharpest and blurriest spot of an image is represented by the absolute color difference variation, and relative color difference variation expresses the variation in the image content. Extensive experiments are performed on five publicly available benchmark synthetic blur databases and two real blur databases, and the results prove that the proposed model work better than the other state-of-the-art and latest NR-IQA models for the prediction accuracy on blurry images. Besides, the model maintains the lowest computational complexity.

关键词： Image quality TV Image color analysis Databases Computational modeling Color Predictive models

Rethinking the Encoder-decoder Structure in Medical Image Segmentation from Releasing Decoder Structure

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Journal of Bionic Engineering 2024年第3期21卷 1511-1521页

作者： Jiajia Ni Wei Mu An Pan Zhengming Chen school of artificial intelligence Anhui Polytechnic UniversityWuhu241000China school of Information Science and Engineering HoHai UniversityChangzhou213000China

Medical image segmentation has witnessed rapid advancements with the emergence of encoder-decoder based *** the encoder-decoder structure,the primary goal of the decoding phase is not only to restore feature map resolution,but also to mitigate the loss of feature information incurred during the encoding ***,this approach gives rise to a challenge:multiple up-sampling operations in the decoder segment result in the loss of feature *** address this challenge,we propose a novel network that removes the decoding structure to reduce feature information loss(CBL-Net).In particular,we introduce a Parallel Pooling Module(PPM)to counteract the feature information loss stemming from conventional and pooling operations during the encoding ***,we incorporate a Multiplexed Dilation Convolution(MDC)module to expand the network's receptive ***,although we have removed the decoding stage,we still need to recover the feature map ***,we introduced the Global Feature Recovery(GFR)*** uses attention mechanism for the image feature map resolution recovery,which can effectively reduce the loss of feature *** conduct extensive experimental evaluations on three publicly available medical image segmentation datasets:DRIVE,CHASEDB and MoNuSeg *** results show that our proposed network outperforms state-of-the-art methods in medical image *** addition,it achieves higher efficiency than the current network of coding and decoding structures by eliminating the decoding component.

关键词： Medical image segmentation Encoder-decoder architecture Attention mechanisms Releasing decoder architecture Neural network

Real-Time Detection and Instance Segmentation of Strawberry in Unstructured Environment

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Computers, Materials & Continua 2024年第1期78卷 1481-1501页

作者： Chengjun Wang Fan Ding Yiwen Wang Renyuan Wu Xingyu Yao Chengjie Jiang Liuyi Ling school of artificial intelligence Anhui University of Science and TechnologyHuainan232001China school of Mechanical Engineering Anhui University of Science and TechnologyHuainan232001China

The real-time detection and instance segmentation of strawberries constitute fundamental components in the development of strawberry harvesting ***-time identification of strawberries in an unstructured envi-ronment is a challenging *** instance segmentation algorithms for strawberries suffer from issues such as poor real-time performance and low *** this end,the present study proposes an Efficient YOLACT(E-YOLACT)algorithm for strawberry detection and segmentation based on the YOLACT *** key enhancements of the E-YOLACT encompass the development of a lightweight attention mechanism,pyramid squeeze shuffle attention(PSSA),for efficient feature ***,an attention-guided context-feature pyramid network(AC-FPN)is employed instead of FPN to optimize the architecture’s ***,a feature-enhanced model(FEM)is introduced to enhance the prediction head’s capabilities,while efficient fast non-maximum suppression(EF-NMS)is devised to improve non-maximum *** experimental results demonstrate that the E-YOLACT achieves a Box-mAP and Mask-mAP of 77.9 and 76.6,respectively,on the custom ***,it exhibits an impressive category accuracy of 93.5%.Notably,the E-YOLACT also demonstrates a remarkable real-time detection capability with a speed of 34.8 *** method proposed in this article presents an efficient approach for the vision system of a strawberry-picking robot.

关键词： YOLACT real-time detection instance segmentation attention mechanism strawberry

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Optics-driven drone

Science China(Information Sciences) 2024年第2期67卷 322-324页

作者： Xuelong LI Guan HUANG Zhigang WANG Bin ZHAO school of artificial intelligence OPtics and Electro Nics (iOPEN)Northwestern Polytechnical University Shanghai artificial intelligence Laboratory

In the field of vicinagearth security, low-altitude flying vehicles such as drones play an indispensable role in aerial remote sensing, intelligent search and rescue, etc. [1]. It can be foreseen that the autonomous and intelligent execution of complex tasks by drones is an inevitable trend for future development.

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ControlService: a containerized solution for control-algorithm-as-a-service in cloud control systems

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Science China(Information Sciences) 2024年第8期67卷 172-189页

作者： Chenggang SHAN Runze GAO Zhen YANG Wei ZHANG Yuanqing XIA school of artificial intelligence Zaozhuang University school of Automation Beijing Institute of Technology

As an extension of networked control systems, cloud control systems(CCSs) have emerged as a new control paradigm to improve the service quality of emerging control missions, such as data-driven modeling and automated vehicles. Existing studies have used the workflow-based restructured method to optimize the computation-intensive algorithms in the CCSs. However, the challenges here are how to define and submit these algorithms' workflows as cloud services and execute these algorithms' workflows in a containerized manner. Based on these challenges, we propose a containerized solution for the control-algorithm-as-a-service(C3aS) in the CCSs, namely Control Service. It offers the control algorithm as a cloud workflow service and uses a customized workflow engine to realize the containerized execution. First, we employ a cloud workflow representation method to define a control algorithm into an abstract cloud workflow form. Afterward, we provide a cloud service representation of the abstract cloud workflow. Next, we design a workflow engine and submit the cloud service to this workflow engine to implement containerized execution of this cloud service in the CCSs. In the experiment, we discuss the cloud service form and containerized implementation of the subspace identification method. Experimental results show that the proposed Control Service has significant performance advantages in computational time, reduction percentage, and speedup ratio compared with the baseline method.

关键词： cloud control systems control-algorithm-as-a-service containerization workflow engine cloud workflow service subspace identification

Intelligent Reflecting Surface-Aided Secure and Covert Communications

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China Communications 2024年第9期 1-10页

作者： Zhou Xiaobo Jiang Yong Xia Tingting Xia Guiyang Shen Tong school of Information and artificial intelligence Anhui Agricultural University

This work employs intelligent reflecting surface(IRS) to enhance secure and covert communication *** formulate an optimization problem to jointly design both the reflection beamformer at IRS and transmit power at transmitter Alice in order to optimize the achievable secrecy rate at Bob subject to a covertness *** first develop a Dinkelbach-based algorithm to achieve an upper bound performance and a high-quality *** reducing the overhead and computational complexity of the Dinkelbach-based scheme,we further conceive a low-complexity algorithm in which analytical expression for the IRS reflection beamforming is derived at each *** result shows that the devised low-complexity algorithm is able to achieve similar secrecy rate performance as the Dinkelbach-based *** examination also shows that introducing an IRS into the considered system can significantly improve the secure and covert communication performance relative to the scheme without IRS.

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Scattering-based hybrid network for facial attribute classification

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Frontiers of Computer Science 2024年第3期18卷 105-116页

作者： Na LIU Fan ZHANG Liang CHANG Fuqing DUAN school of artificial intelligence Beijing Normal UniversityBeijing 100875China

Face attribute classification(FAC)is a high-profile problem in biometric verification and face *** recent research has been devoted to extracting more delicate image attribute features and exploiting the inter-attribute correlations,significant challenges still *** scattering transform(WST)is a promising non-learned feature *** has been shown to yield more discriminative representations and outperforms the learned representations in certain *** to the image classification task,WST can enhance subtle image texture information and create local deformation *** paper designs a scattering-based hybrid block,to incorporate frequency-domain(WST)and image-domain features in a channel attention manner(Squeezeand-Excitation,SE),termed WS-SE *** with CNN,WS-SE achieves a more efficient FAC performance and compensates for the model sensitivity of the small-scale affine *** addition,to further exploit the relationships among the attribute labels,we propose a learning strategy from a causal *** cause attributes defined using the causalityrelated information can be utilized to infer the effect attributes with a high confidence *** analysis experiments demonstrate the effectiveness of our model,and our hybrid model obtains state-of-the-art results in two public datasets.

关键词： wavelet scattering transform causality-related learning facial attribute classification

Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 37-57页

作者： Zhiqiang Pu Yi Pan Shijie Wang Boyin Liu Min Chen Hao Ma Yixiong Cui the school of artificial intelligence University of Chinese Academy of Sciences the Institute of Automation Chinese Academy of Sciences the Nanjing artificial intelligence Research of IA the school of Sports Engineering Beijing Sport University

Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) *** addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.

关键词： artificial intelligence(AI) decision-making football review soccer sports analytics

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