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Lightweight Transfer Learning Models for Ultrasound-Guided Classification of COVID-19 Patients

computers, Materials & Continua 2021年第11期69卷 2295-2312页

作者： Mohamed Esmail Karar Omar Reyad Mohammed Abd-Elnaby Abdel-Haleem Abdel-Aty Marwa Ahmed Shouman College of Computing and Information Technology Shaqra UniversityShaqra11961Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering(FEE)Menoufia UniversityMenouf32952Egypt Department of Mathematics and Computer Science Faculty of ScienceSohag UniversitySohag82524Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Physics College of SciencesUniversity of BishaBisha61922Saudi Arabia Department of Physics Faculty of ScienceAl-Azhar UniversityAssiut71524Egypt Department of Computer Science and Engineering Faculty of Electronic Engineering(FEE)Menoufia UniversityMenouf32952Egypt

Lightweight deep convolutional neural networks(CNNs)present a good solution to achieve fast and accurate image-guided diagnostic procedures of COVID-19 ***,advantages of portable Ultrasound(US)imaging such as simplicity and safe procedures have attracted many radiologists for scanning suspected COVID-19 *** this paper,a new framework of lightweight deep learning classifiers,namely COVID-LWNet is proposed to identify COVID-19 and pneumonia abnormalities in US *** to traditional deep learning models,lightweight CNNs showed significant performance of real-time vision applications by using mobile devices with limited hardware *** main lightweight deep learning models,namely MobileNets,ShuffleNets,MENet and MnasNet have been proposed to identify the health status of lungs using US *** image dataset(POCUS)was used to validate our proposed COVID-LWNet framework *** classes of infectious COVID-19,bacterial pneumonia,and the healthy lung were investigated in this *** results showed that the performance of our proposed MnasNet classifier achieved the best accuracy score and shortest training time of 99.0%and 647.0 s,*** paper demonstrates the feasibility of using our proposed COVID-LWNet framework as a new mobilebased radiological tool for clinical diagnosis of COVID-19 and other lung diseases.

关键词： Coronavirus medical image processing artificial intelligence ultrasound

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Multi-Band Low-Profile Non-Uniform Metasurface Antenna for Sub-6-GHz Applications

Multi-Band Low-Profile Non-Uniform Metasurface Antenna for S...

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World Congress on Computing and Communication Technologies (WCCCT)

作者： Naveed Hamid Nawaz Khan Botao Feng Li Deng Wei Yang Xiao Ding Qingsheng Zeng College of Electronics and Information Engineering Shenzhen University Shenzhen China College of Information and CommunicationEngineering Beijing University of Posts and Telecommunications Beijing China College of Big Data and Internet Shenzhen Technology University Shenzhen China Faculty of Humanities and Arts Macau University of Science and Technology Macau China Department of Computer and Engineering University of Quebec in Outaouais Quebec Canada

ISBN: (数字)9798331512620

ISBN: (纸本)9798331512637

This paper presents the design of a compact nonuniform metasurface antenna with dimensions of 70×70 mm 2 . The antenna basically comprises a 1.6 mm-thick metasurface patch and a 1 mm-thick substrate, separated by a 5-mm air gap to enhance performance. The proposed design is analyzed using CST Microwave Studio, evaluating key parameters such as Voltage Standing Wave Ratio (VSWR), |S11|, and radiation efficiency. Simulation results indicate excellent impedance matching, with |S11| below −10 dB across 2.35 GHz to 6 GHz, reaching a minimum of −36.647 dB at 5.16 GHz. The VSWR remains below 2.5, with a minimum of 1.5 at 5.16 GHz. Additionally, the antenna demonstrates high radiation efficiency, ranging 74% to 80.7%, indicating effective energy radiation. The experiment results highlight the potential of the proposed non-uniform metasurface antenna for next-generation wireless communication systems, especially for 5G and beyond, where compact size, broad bandwidth, and high efficiency are essential. Notably, the integration of a non-uniform metasurface geometry and strategically placed air gap enhances overall performance, making it a promising candidate for future wireless technologies.

关键词： Wireless communication 5G mobile communication Impedance matching Simulation Air gaps Voltage Metasurfaces Antennas Substrates Next generation networking

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Estimating the AGV load and a battery lifetime based on the current measurement and random forest application

Estimating the AGV load and a battery lifetime based on the ...

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IEEE International Conference on Big Data

作者： Krzysztof Hanzel Damian Grzechca Adam Ziebinski Lukas Chruszczyk Artur Janus Department of Telecommunications and Teleinformatics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Department of Electronics Electrical Engineering and Microelectronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Department of Distributed Systems and Informatics Devices Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Student of Electrical Engineering Faculty of Electrical Engineering Silesian University of Technology Gliwice Poland

The paper describes the energy consumption from the battery based on the current measurements for various cases, i.e., speed (PWL adjustment) and loads. The main purpose of the research is to have additional and reliable information about power consumption and battery life estimation for autonomous guided vehicles (AGV). The authors propose a two-step algorithm. In the first step, a linear classifier was proposed. Then, the KNN classifier was tested; however, it did not give satisfactory results, so it was finally decided to use the random forest to estimate the load and PWL. The time domain current measurement is evaluated, and the beforementioned algorithms process the selected statistical measures. It has been proven that a two-step algorithm allows for achieving high accuracy. Based on the current observation, the paper is a good starting point for further investigation of the AGV because it is usually implemented in the AGV – so it does not require additional hardware. Moreover, it can lead to better energy management and increase battery lifetime.

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Deep Robust Reversible Watermarking

arXiv

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arXiv 2025年

作者： Chen, Jiale Wang, Wei Shi, Chongyang Dong, Li Li, Yuanman Hu, Xiping School of Computer Science Beijing Institute of Technology Beijing100081 China Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen518172 China School of Medical Technology Beijing Institute of Technology Beijing100081 China College of Electronics and Information Engineering Shenzhen University Shenzhen518060 China Department of Computer Science Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China

Robust Reversible Watermarking (RRW) enables perfect recovery of cover images and watermarks in lossless channels while ensuring robust watermark extraction under lossy channels. However, existing RRW methods, mostly non-deep learning-based, suffer from complex designs, high computational costs, and poor robustness limiting their practical applications. To address these issues, this paper proposes Deep Robust Reversible Watermarking (DRRW), a deep learning-based RRW scheme. DRRW introduces an Integer Invertible Watermark Network (iIWN) to achieve an invertible mapping between integer data distributions, fundamentally addressing the limitations of conventional RRW approaches. Unlike traditional RRW methods requiring task-specific designs for different distortions, DRRW adopts an encoder-noise layer-decoder framework, enabling adaptive robustness against various distortions through end-to-end training. During inference, the cover image and watermark are mapped into an overflowed stego image and latent variables. Arithmetic coding efficiently compresses these into a compact bitstream, which is embedded via reversible data hiding to ensure lossless recovery of both the image and watermark. To reduce pixel overflow, we introduce an overflow penalty loss, significantly shortening the auxiliary bitstream while improving both robustness and stego image quality. Additionally, we propose an adaptive weight adjustment strategy that eliminates the need to manually preset the watermark loss weight, ensuring improved training stability and performance. Experiments on multiple datasets demonstrate that DRRW achieves notable performance advantages. Compared to state-of-the-art RRW methods, DRRW improves robustness and reduces embedding, extraction, and recovery complexities by 55.14×, 5.95×, and 3.57×, respectively. The auxiliary bitstream is shortened by 43.86×, and reversible embedding succeeds on 16,762 images in the PASCAL VOC 2012 dataset, marking a significant step toward pra

关键词： Image enhancement

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Study on an Adaptive Clamping Device for Passive Safety Delivery of Vascular Intervention Robot

Study on an Adaptive Clamping Device for Passive Safety Deli...

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IEEE International Conference on Mechatronics and Automation

作者： Sheng Cao Shuxiang Guo Jian Guo Jian Wang Chunying Li Huiyin Xu Bin Wang Mingchao Ding Aerospace Center Hospital & the Key Laboratory of Convergence Medical Engineering System and Healthcare Technology School of Life Science & Ministry of Industry and Information Technology Beijing Institute of Technology Beijing China Shenzhen Institute of Advanced Biomedical Robot Company Limited Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China National Engineering Laboratory of Computer Technology for Big Data Systems Shenzhen University Shenzhen China

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

In practical clinical applications, vascular intervention surgical robots have developed sophisticated human-machine interaction systems, enabling assistance to physicians in performing remote surgeries and providing intelligent visual feedback. However, regarding surgical safety, current research predominantly focuses on force feedback and robot control logic, with clamping mechanisms targeting the locking of catheters and guide wires. Excessive clamping force may lead to surface damage to intervention instruments, while insufficient force delivery may result from slippery surfaces. Therefore, addressing these issues, this study proposed a passive, compliant safety strategy for an adaptive clamping device based on a vascular intervention surgical robot platform. This device can accommodate different diameter catheters and maintain a constant delivery force during the intervention process. Finally, through experimentation, the effectiveness, safety, and stability of the device were demonstrated.

关键词： Visualization Medical robotics Force Wires Robot control Surgery Safety

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Generalized Test Suite for Continuous Dynamic Multi-objective Optimization 11th

Generalized Test Suite for Continuous Dynamic Multi-objectiv...

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11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021

作者： Shao, Chang Zhao, Qi Shi, Yuhui Jiang, Jing Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Faculty of Engineering and Information Technology University of Technology Sydney Ultimo Australia School of Computer Science and Technology University of Science and Technology of China Hefei230027 China

ISBN: (纸本)9783030720612

Dynamic multi-objective optimization (DMO) has recently attracted increasing interest. Suitable benchmark problems are crucial for evaluating the performance of DMO solvers. However, most of the existing DMO benchmarks mainly focus on Pareto-optimal solutions (PS) varying on the hyperplane, which may produce some unexpected bias for algorithmic analysis. Furthermore, they do not comprehensively consider the general time-linkage property, yet which is commonly observed in real-world applications. To alleviate these two issues, we designed a generalized test suite (GTS) for DMO with the following two advantages over previous existing benchmarks: 1) the PS can change on the hypersurface over time, to better compare the tracking ability of different DMO solvers;2) the general time-linkage feature is included to systemically investigate the algorithmic robustness in the dynamic environment. Experimental results on five representative DMO algorithms demonstrated the proposed GTS can efficiently discriminate the performance of DMO algorithms and is more general than existing benchmarks. © 2021, Springer Nature Switzerland AG.

关键词： Pareto principle

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Multi-scale Context Intertwining for Panoramic Renal Pathology Segmentation

Multi-scale Context Intertwining for Panoramic Renal Patholo...

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

作者： Ye Zhang Xianchao Guan Hengrui Li Xiangming Yan Ziyue Wang Yongbing Zhang School of Computer Science and Technology Harbin Institute of Technology Shenzhen Leibniz-Institut für Analytische Wissenschaften ISAS - e.V. Pengcheng Laboratory Shenzhen Faculty of Computing Harbin Institute of Technology Department of Electronic and Computer Engineering National University of Singapore

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Panoramic segmentation of renal pathological tissues plays a crucial role in diagnosing renal carcinoma and other kidney-related diseases. The multi-scale nature of kidney tissues, which requires different magnification levels for accurate analysis, presents a significant challenge for segmentation models. In this work, we propose a Multi-scale Context Intertwining Network (MCINet) to address this issue. Our approach utilizes an auxiliary interaction network to enhance feature interaction between different scales and generate pseudo-labels for unannotated structures. By incorporating exponential moving average strategies, we ensure seamless feature integration across scales. Extensive experiments demonstrate that MCINet outperforms state-of-the-art models in key metrics such as Dice and Hausdorff Distance, proving its efficacy in renal tissue segmentation tasks.

关键词： Measurement Image segmentation Pathology Analytical models Signal processing Acoustics Speech processing Optimization Kidney Diseases

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SpikingYOLOX: Improved YOLOX Object Detection with Fast Fourier Convolution and Spiking Neural Networks 39

SpikingYOLOX: Improved YOLOX Object Detection with Fast Four...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Miao, Wei Shen, Jiangrong Xu, Qi Hamalainen, Timo Xu, Yi Cong, Fengyu School of Computer Science and Technology Dalian University of Technology China Faculty of Information Technology University of Jyväskylä Finland School of Computer Science and Technology Xi'an Jiaotong University China State Key Lab of Brain-Machine Intelligence Zhejiang University China School of Control Science and Engineering Dalian University of Technology China School of Biomedical Engineering Dalian University of Technology China

ISBN: (纸本)157735897X

In recent years, with the advancements in brain science, spiking neural networks (SNNs) have garnered significant attention. SNNs can generate spikes that mimic the function of neurons transmission in humans brain, thereby significantly reducing computational costs by the event-driven nature during training. While deep SNNs have shown impressive performance on classification tasks, they still face challenges in more complex tasks such as object detection. In this paper, we propose SpikingYOLOX, extending the structure of the original YOLOX by introducing signed spiking neurons and fast Fourier convolution (FFC). The designed ternary signed spiking neurons could generate three kinds of spikes to obtain more robust features in the deep layer of the backbone. Meanwhile, we integrate FFC with SNN modules to enhance object detection performance, because its global receptive field is beneficial to the object detection task. Extensive experiments demonstrate that the proposed SpikingYOLOX achieves state-of-the-art performance among other SNN-based object detection methods. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Deep neural networks

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Accurate and Efficient Privacy-Preserving Feature Extraction on Encrypted Images

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IEEE Transactions on Dependable and Secure Computing 2025年

作者： Zheng, Peijia Fang, Xiongjie Zhou, Zhipeng Yang, Rui Lu, Wei Cao, Xiaochun Huang, Jiwu Sun Yat-Sen University School of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology MoE Key Laboratory of Information Technology Guangzhou510006 China Alibaba Group Hanzhou311121 China Shenzhen Campus of Sun Yat-sen University School of Cyber Science and Technology Shenzhen518100 China Shenzhen MSU-BIT University Guangdong Laboratory of Machine Perception and Intelligent Computing Faculty of Engineering Shenzhen518116 China

In cloud computing, it is necessary to outsource image processing algorithms securely without exposing private image content. The scale-invariant feature transform (SIFT) is a famous local descriptor widely used in computer vision. There are already some privacy-preserving schemes for computing SIFT on encrypted images. However, the state-of-the-art works have to convert fixed-point numbers into their binary representations, which reduces efficiency and accuracy. In this paper, we propose a novel privacy-preserving SIFT scheme built from secure protocols designed explicitly for fixed-point numbers to solve this problem. Specifically, using RLWE-based homomorphic encryption, we propose word-wise protocols to perform secure division, square root operation, comparison, derivation, and matrix inversion in a single-instruction multiple-data manner. These protocols allow direct processing of fixed-point numbers without converting them to binary numbers, thus achieving high computational efficiency. We have also realized critical SIFT steps missing from previous works, including Euclidean gradient amplitude computation, histogram peak interpolation, and precise interval localization, leading to improved accuracy of SIFT features in the encrypted domain. We conduct security analysis and perform extensive experiments to evaluate the execution efficiency and accuracy. The experimental results show that the proposed scheme outperforms the state-of-the-art works in terms of computational efficiency and accuracy. © 2004-2012 IEEE.

关键词： Differential privacy

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Two Factors that Influence Our Selection of Digital Avatars: Gender Performativity and Historical Culture 5th

Two Factors that Influence Our Selection of Digital Avatars:...

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5th International Conference on Smart Vehicular technology, Transportation, Communication and Applications, VTCA 2022

作者： Liu, Shutang Li, Yongyu Li, Minggui Guan, Yin Jiang, Hang Jiang, Lei Faculty of Humanities and Arts Macau University of Science and Technology 999078 China Academic Affairs Office Minjiang University Fuzhou China College of Computer and Control Engineering Minjiang University Fuzhou China College of Mathematics and Data Science Minjiang University Fuzhou China Culture and Creation Department Fuzhou Polytechnic Fuzhou China

ISBN: (纸本)9789819908479

In this study, 74 college student volunteers were recruited as experimental participants, and 108 game 3D images of the Arena of Valor game were used as the selected samples. The digital avatar is presented to the subject through AR technology. Then, the participants were asked to choose five digital avatar that they would probably go on to use in the future metaverse. Finally, after excluding the effects of game familiarity and other socio-statistical variables, it was found that the gender of the selected Digital avatar was positively correlated with the actual participants’ gender, and it was further found that females were more gender specific and more aggregated in terms of Gender Expression than males, while males were less gender specific and more dispersed. This study found that although there was certain influence of historical culture on the selection aspect of the digital avatar, it was not significant. Local game characters and Japanese game characters have equally important influence. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Students

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