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Deep Semantic and Attentive Network for Unsupervised Video Summarization

ACM Transactions on Multimedia Computing, Communications and Applications 2022年第2期18卷 1-21页

作者： Zhong, Sheng-Hua Lin, Jingxu Lu, Jianglin Fares, Ahmed Ren, Tongwei College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical Engineering Computer Systems Engineering Program Faculty of Engineering at Shoubra Benha University Cairo Egypt State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China

With the rapid growth of video data, video summarization is a promising approach to shorten a lengthy video into a compact version. Although supervised summarization approaches have achieved state-of-the-art performance, they require frame-level annotated labels. Such an annotation process is time-consuming and tedious. In this article, we propose a novel deep summarization framework named Deep Semantic and Attentive Network for Video Summarization (DSAVS) that can select the most semantically representative summary by minimizing the distance between video representation and text representation without any frame-level labels. Another challenge associated with video summarization tasks mainly originates from the difficulty of considering temporal information over a long time. Long Short-Term Memory (LSTM) performs well for temporal dependencies modeling but does not work well with long video clips. Therefore, we introduce a self-attention mechanism into our summarization framework to capture the long-range temporal dependencies among the frames. Extensive experiments on two popular benchmark datasets, i.e., SumMe and TVSum, show that our proposed framework outperforms other state-of-the-art unsupervised approaches and even most supervised methods. © 2022 Association for Computing Machinery.

关键词： Semantics

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Continual learning with Bayesian model based on a fixed pre-trained feature extractor

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Visual Intelligence 2023年第1期1卷 1-14页

作者： Yang, Yang Cui, Zhiying Xu, Junjie Zhong, Changhong Zheng, Wei-Shi Wang, Ruixuan School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Department of Network Intelligence Peng Cheng Laboratory Shenzhen China Key Laboratory of Machine Intelligence and Advanced Computing MOE Guangzhou China

Deep learning has shown its human-level performance in various applications. However, current deep learning models are characterized by catastrophic forgetting of old knowledge when learning new classes. This poses a challenge such as in intelligent diagnosis systems where initially only training data of a limited number of diseases are available. In this case, updating the intelligent system with data of new diseases would inevitably downgrade its performance on previously learned diseases. Inspired by the process of learning new knowledge in human brains, we propose a Bayesian generative model for continual learning built on a fixed pre-trained feature extractor. In this model, knowledge of each old class can be compactly represented by a collection of statistical distributions, e.g., with Gaussian mixture models, and naturally kept from forgetting in continual learning over time. Unlike existing class-incremental learning methods, the proposed approach is not sensitive to the continual learning process and can be additionally well applied to the data-incremental learning scenario. Experiments on multiple medical and natural image classification tasks reveal that the proposed approach outperforms state-of-the-art approaches that even keep some images of old classes during continual learning of new classes. © The Author(s) 2023.

关键词： Bayesian model Continual learning Fixed feature extractor Generative approach

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An Injection Circuit Coupling Low-DC Voltage Impedance Matching System With Flexible Resonance Points for Square-Wave Voltage Power Amplifier in EM Exploration

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IEEE Transactions on Power Electronics 2025年第8期40卷 11032-11050页

作者： Pang, Ying Zhu, Yongji Ji, Yanju Li, Gang Xiang, Zeng Gong, Cheng Han, Rong Tian, Wei Guo, Qun Wong, Man-Chung Lin, Jun Jilin University State Key Laboratory of Deep Earth Exploration and Imaging College of Instrumentation and Electrical Engineering Changchun130026 China Jilin University College of Instrumentation and Electrical Engineering Changchun130021 China Tongda Electromagnetic Energy Company Ltd. Changsha410000 China University of Macau State Key Laboratory of Analog and Mixed-Signal VLSI 999078 China University of Macau Institute of Microelectronics 999078 China University of Macau Department of Electrical and Computer Engineering Faculty of Science and Technology 999078 China Dalian University of Technology School of Optoelectronic Engineering and Instrumentation Science Dalian116024 China Guangxi University School of Electrical Engineering Nanning530000 China Dalian Maritime University College of Marine Electrical Engineering Dalian116000 China University of Macau State Key Laboratory of Internet of Things for Smart City 999078 China

This article focuses on reactive power compensation and impedance matching of square-wave voltages. Square-wave voltage is the operating voltage in electromagnetic method (EM) exploration. The characteristics of a square-wave voltage are very different from those of a sinusoidal voltage in the power grid. Although some papers proposed impedance matching converters for square-wave voltages, they solved the high dc voltage requirement problem. The problem is caused by square-wave voltage having multiple and variable spectral components. An impedance-matching converter with an injection circuit (IMFR) for square-wave voltage is proposed. IMFR is composed of a thyristor-controlled inductor and capacitor (TCLC) part and injection circuit coupling active H-bridge part. TCLC can be controlled to resonate at the highest energy fundamental frequency for damping the largest part of the dc voltage requirement. The use of TCLC offsets the varying fundamental frequency demand on the dc voltage. First, this article gives a joint design and optimization approach for the lowest dc voltage requirement. Second, a synergistic control method of proposed IMFR is provided implementing IMFR. Third, two groups of comparative experiments show that the proposed IMFR can enlarge the current by 11.8%-38.5%. The effect on the current increase is 4.4%-7.9% higher than using only the H-bridge of the previous method when they are operated with the same dc voltage. © 1986-2012 IEEE.

关键词： Natural frequencies

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Efficient Segmentation Approach for Different Medical Image Modalities

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computers, Materials & Continua 2022年第11期73卷 3119-3135页

作者： Walid El-Shafai Amira A.Mahmoud El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

This paper presents a study of the segmentation of medical *** paper provides a solid introduction to image enhancement along with image segmentation *** the first step,the morphological operations are employed to ensure image detail protection and *** objective of using morphological operations is to remove the defects in the texture of the ***,the Fuzzy C-Means(FCM)clustering algorithm is used to modify membership function based only on the spatial neighbors instead of the distance between pixels within local spatial neighbors and cluster *** proposed technique is very simple to implement and significantly fast since it is not necessary to compute the distance between the neighboring pixels and the cluster *** is also efficient when dealing with noisy images because of its ability to efficiently improve the membership partition *** results are performed on different medical image ***(Us),X-ray(Mammogram),Computed Tomography(CT),Positron Emission Tomography(PET),and Magnetic Resonance(MR)images are the main medical image modalities used in this *** obtained results illustrate that the proposed technique can achieve good results with a short time and efficient image *** results on different image modalities show that the proposed technique can achieve segmentation accuracies of 98.83%,99.71%,99.83%,99.85%,and 99.74%for Us,Mammogram,CT,PET,and MRI images,respectively.

关键词： Image segmentation ultrasonic mammogram CT PET MRI morphological operations FCM active contours

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Review on guidance and control of aerospace vehicles: recent progress and prospect

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Aerospace Systems 2024年第2期7卷 175-192页

作者： Wang, Zian Cai, Pengcheng Gong, Zheng Zhang, Chengxi Zhao, Shunyi Wu, Jin Dong, Peng Department of Aerospace Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China Key Laboratory of Advanced Control for Light Industry Processes Ministry of Education Jiangnan University Wuxi214122 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai China

This paper expounds on the development status and relevant works of control and guidance methods of the aerospace vehicle in recent years. The control difficulties and the solutions in the related results are introduced briefly. Moreover, the guidance methods are then expounded in detail according to the flight phases of the whole flight mission. Guidance methods are usually included in each phase, and the corresponding trajectory design theories are also introduced where necessary. In addition, the potential future development direction prospects. Based on the above, a brief conclusion is then made as a summary. © Shanghai Jiao Tong University 2024.

关键词： Space flight

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Software-Defined Ultrasonic Communication System using PPM-EMAT with High Transmission Rate

Software-Defined Ultrasonic Communication System using PPM-E...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Huang, Xin Saniie, Jafar Bakhtiari, Sasan Heifetz, Alexander Illinois Institute of Technology Ecasp Research Laboratory Department of Electrical and Computer Engineering ChicagoIL United States Argonne National Laboratory Nuclear Science and Engineering Division LemontIL United States

ISBN: (纸本)9798350346459

A novel approach to ultrasonic communication systems introduces a software-defined system that utilizes Periodic-permanent-magnet electromagnetic acoustic transducers (PPM-EMATs) as transmitters and receivers. Traditional systems had limitations in adaptability and flexibility. The software-defined system provides enhanced versatility, adaptability, and portability, allowing customization for diverse applications. The use of PPM-EMATs is explored for optimizing energy transfer through metal plate channels, generating shear horizontal waves. Experimental tests validate the efficiency of PPM-EMATs, showing successful communication at a 10-kbps bitrate using ASK modulation with a high signal-to-noise ratio (SNR). The research highlights the potential of PPM-EMAT technology in high-speed software-defined ultrasonic communication systems. © 2023 IEEE.

关键词： Signal to noise ratio

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Hybrid Segmentation Approach for Different Medical Image Modalities

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computers, Materials & Continua 2022年第11期73卷 3454-3471页

作者： Walid El-Shafai Amira A.Mahmoud El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

The segmentation process requires separating the image region into sub-regions of similar *** sub-region has a group of pixels having the same characteristics,such as texture or *** paper suggests an efficient hybrid segmentation approach for different medical image modalities based on particle swarm optimization(PSO)and improved fast fuzzy C-means clustering(IFFCM)*** extensive comparative study on different medical images is presented between the proposed approach and other different previous segmentation *** existing medical image segmentation techniques incorporate clustering,thresholding,graph-based,edge-based,active contour,region-based,and watershed *** paper extensively analyzes and summarizes the comparative investigation of these ***,a prediction of the improvement involves the combination of these techniques is *** obtained results demonstrate that the proposed hybrid medical image segmentation approach provides superior outcomes in terms of the examined evaluation metrics compared to the preceding segmentation techniques.

关键词： Image segmentation ultrasonic images X-ray images CT images PET images MR images fuzzy c-mean morphological operations active contour

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Optimization of Microwave Resonant Cavity Flowmeter Design for High Temperature Fluid Sensing Applications

Optimization of Microwave Resonant Cavity Flowmeter Design f...

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2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Fang, Tianyang Saniie, Jafar Bakhtiari, Sasan Heifetz, Alexander Illinois Institute of Technology Ecasp Research Laboratory Department of Electrical and Computer Engineering ChicagoIL United States Nuclear Science and Engineering Division Argonne National Laboratory LemontIL United States

ISBN: (纸本)9781665493765

This paper investigates optimization of parameters to enhance performance of a microwave resonant cavity transducer for high temperature fluid flow sensing in advanced reactors. The cylindrical microwave cavity flowmeter is a novel sensor that measures fluid flow velocity through deflection of the cavity wall due to dynamic fluid pressure. This sensor is designed to operate in harsh environments of a nuclear reactor because sensor material is resilient to high temperatures, ionizing radiation, and corrosion. Parameters that determine performance characteristics of the transducer include dimensions of the microwave cavity, cavity electromagnetic excitation method, and cavity material. We investigate transducer design through computer simulations, with the objective of maximizing cavity Q-factor. © 2023 IEEE.

关键词： Microwave resonators

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SAR Images Change Detection Based on Attention Mechanism-Convolutional Wavelet Neural Network

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 12133-12149页

作者： Jiahui, J.E. Wang, Lu Zhao, Chunhui Mathiopoulos, P. Takis Ohtsuki, Tomoaki Adachi, Fumiyuki Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Ministry of Industry and Information Technology Key Laboratory of Advanced Marine Communication and Information Technology Harbin150001 China National and Kapodistrian University of Athens Department of Informatics and Telecommunications 15772 Greece Keio University Department of Information and Computer Science Kanagawa 2238522 Japan Tohoku University International Research Institute of Disaster Science Sendai9808576 Japan

As synthetic aperture radar (SAR) image change detection can continuously acquire target information under all weather conditions, it has been used in the past for various applications. However, it is very challenging to use SAR images for small area change detection due to the presence of noise and the imbalance between classes. To deal with these problems this article proposes a SAR images change detection scheme which is based upon an Attention Mechanism and Convolutional Wavelet Neural Network. First, employing Multiscale Superpixel Reconstructed Difference Image effectively enhances the edge information of the images. Second, a two-stage Weighted Center Constrained Fuzzy C-Means clustering algorithm is proposed. To constrain incorrect migration in the subsequent clustering phase, the algorithm uses a two-stage clustering algorithm. During the first stage weights in the clustering process to improve the accuracy of the resulting clustering centers are introduced while during the second stage, these refined cluster centers can be constrained. Third, a Convolutional Squeeze-and-Excitation Attention Mechanism Wavelet Neural Network (CSWNN) is proposed which more accurately distinguishes uncertain pixels and thus reduces redundant features. The final Denoising Diffusion Probabilistic Model is introduced into the CSWNN to expand pseudolabeled samples. Comparing this algorithm with seven sets of contrast experiments on six real SAR datasets shows that the accuracy of detecting changes in small regions is 2% –9% better than the classical algorithm. © 2008-2012 IEEE.

关键词： Convolutional neural networks

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Boosting efficiency and stability of 2D alternating cation perovskite solar cells via rational surface-modification: Marked passivation efficacy of anion

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Journal of Energy Chemistry 2023年第9期84卷 354-362页

作者： Hualin Zheng Xuefeng Peng Tingxi Chen Ting Zhang Shihao Yuan Lei Wang Feng Qian Jiang Huang Xiaodong Liu Zhi David Chen Yanning Zhang Shibin Li State Key Laboratory of Electronic Thin Films and Integrated Devices and School of Optoelectronic Science and EngineeringUniversity of Electronic Science and Technology of China(UESTC)Chengdu 610054SichuanChina Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China(UESTC)Chengdu 610054SichuanChina Department of Electrical&Computer Engineering and Center for Nanoscale Science&EngineeringUniversity of KentuckyLexingtonKY 40506USA Institute of Electronic and Information Engineering of UESTC in Guangdong Dongguan 523808GuangdongChina

Two-dimensional(2D) alternating cation(ACI) perovskite surface defects,especially dominant iodine vacancies(V_Ⅰ) and undercoordinated Pb^(2+),limit the performance of perovskite solar cells(PVSCs).To address the issue,1-butyl-3-methylimidazolium trifluoro-methane-sulfonate(BMIMOTF) and its iodide counterpart(BMIMI) are utilized to modify the perovskite surface *** find that BMIMI can change the perovskite surface,whereas BMIMOTF shows a nondestructive and more effective defect passivation,giving significantly reduced defect density and suppressed charge-carrier nonradiative *** mainly attributes to the marked passivation efficacy of OTF-anion on V_Ⅰ and undercoordinated Pb^(2+),rather than BMIMI^(+) *** from the rational surface-modification of BMMIMOTF,the films exhibit an optimized energy level alignment,enhanced hydrophobicity and suppressed ion ***,the BMIMOTF-modified devices achieve an impressive efficiency of 21.38% with a record open-circuit voltage of 1.195 V,which is among the best efficiencies reported for 2D PVSCs,and display greatly enhanced humidity and thermal stability.

关键词： 2D ACI perovskite solar cells Charge-carrier nonradiative recombination Surface defects passivation Energy level alignment Ionic migration Stability

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