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Event-Driven Attention Network:A Cross-Modal Framework for Efficient Image-Text Retrieval in Mass Gathering Events

computers, Materials & Continua 2025年第5期83卷 3277-3301页

作者： Kamil Yasen Heyan Jin Sijie Yang Li Zhan Xuyang Zhang Ke Qin Ye Li School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China School of Information and Software Engineering University of Electronic Science and Technology ofChinaChengdu611731China Kashi Institute of Electronics and Information Industry Kashi844508China

Research on mass gathering events is critical for ensuring public security and maintaining social ***,most of the existing works focus on crowd behavior analysis areas such as anomaly detection and crowd counting,and there is a relative lack of research on mass gathering *** believe real-time detection and monitoring of mass gathering behaviors are essential formigrating potential security risks and ***,it is imperative to develop a method capable of accurately identifying and localizing mass gatherings before disasters occur,enabling prompt and effective *** address this problem,we propose an innovative Event-Driven Attention Network(EDAN),which achieves image-text matching in the scenario of mass gathering events with good results for the first *** image-text retrieval methods based on global alignment are difficult to capture the local details within complex scenes,limiting retrieval *** local alignment-based methods aremore effective at extracting detailed features,they frequently process raw textual features directly,which often contain ambiguities and redundant information that can diminish retrieval efficiency and degrade model *** overcome these challenges,EDAN introduces an Event-Driven AttentionModule that adaptively focuses attention on image regions or textual words relevant to the event *** calculating the semantic distance between event labels and textual content,this module effectively significantly reduces computational complexity and enhances retrieval *** validate the effectiveness of EDAN,we construct a dedicated multimodal dataset tailored for the analysis of mass gathering events,providing a reliable foundation for subsequent *** conduct comparative experiments with other methods on our dataset,the experimental results demonstrate the effectiveness of *** the image-to-text retrieval task,EDAN achieved the best performance on the R@5 metric,w

关键词： Mass gathering events image-text retrieval attention mechanism

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Hardware-friendly rate estimation algorithm and architecture design for AVS3

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Multimedia Tools and Applications 2025年 1-19页

作者： Yan, Yunyao Xiang, Guoqing Chen, Jie Huang, Xiaofeng Zhang, Peng Jia, Huizhu Xie, Xiaodong School of Electronic and Computer Engineering Peking University Shenzhen China School of Computer Science Peking University Beijing China Advanced Institute of Information Technology Peking University Hangzhou China School of Communication Engineering Hangzhou Dianzi University Hangzhou China

To enhance the capabilities of advanced video coding for emerging applications, the AVS3 standard has been introduced to double the coding efficiency compared to its predecessor, the AVS2 standard. It incorporates sophisticated coding tools, such as advanced rate-distortion optimization (RDO), to select the optimal coding mode. The AVS3 standard further refines bit rate compression through Advanced Entropy Coding (AEC) within the RDO process. However, AEC demands significant computational resources due to its high data dependency and involves complex steps like binarization, context modeling, interval subdivision, renormalization, handling of outstanding bits, and context updating. Notably, the time complexity of AEC is predominantly due to context updating and interval subdivision, which are recursive and thus pose challenges for real-time applications, particularly in hardware implementations. Addressing these challenges, this paper introduces an adaptive rate estimation algorithm using a hardware-friendly piece-wise linear function to expedite bit rate calculations for AVS3 applications. Initially, we develop a linear rate estimation method based on the statistics of bin numbers. To preserve high coding performance, we further propose an adaptive model parameter updating method that adjusts weights dynamically based on varying video content. Building on this fast rate estimation algorithm, we propose a high-throughput hardware architecture that incorporates pipelining and parallelization to meet the stringent real-time requirements for 4K@120fps ultra-high-definition video at 200 MHz, with only a minimal increase in BD-rate by 1.06% under the All-Intra (AI) configuration. To our knowledge, this is the pioneering study focusing on hardware-oriented rate estimation for the AVS3 standard, marking a significant advancement in the field of video coding technology. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature

关键词： Video signal processing

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Data-driven output regulation control for constrained linear systems

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Science China(Information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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DIEONet:Domain-Invariant Information Extraction and Optimization Network for Visual Place Recognition

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computers, Materials & Continua 2025年第3期82卷 5019-5033页

作者： Shaoqi Hou Zebang Qin Chenyu Wu Guangqiang Yin Xinzhong Wang Zhiguo Wang School of Computer Science and Technology Xinjiang UniversityUrumqi830046China School of Information and Software Engineering University of Electronic Science and Technology ofChinaChengdu611731China Institute of Public Security Kash Institute of Electronics and Information IndustryKashi844000China

Visual Place Recognition(VPR)technology aims to use visual information to judge the location of agents,which plays an irreplaceable role in tasks such as loop closure detection and *** is well known that previous VPR algorithms emphasize the extraction and integration of general image features,while ignoring the mining of salient features that play a key role in the discrimination of VPR *** this end,this paper proposes a Domain-invariant Information Extraction and Optimization Network(DIEONet)for *** core of the algorithm is a newly designed Domain-invariant Information Mining Module(DIMM)and a Multi-sample Joint Triplet Loss(MJT Loss).Specifically,DIMM incorporates the interdependence between different spatial regions of the feature map in the cascaded convolutional unit group,which enhances the model’s attention to the domain-invariant static object *** Loss introduces the“joint processing of multiple samples”mechanism into the original triplet loss,and adds a new distance constraint term for“positive and negative”samples,so that the model can avoid falling into local optimum during *** demonstrate the effectiveness of our algorithm by conducting extensive experiments on several authoritative *** particular,the proposed method achieves the best performance on the TokyoTM dataset with a Recall@1 metric of 92.89%.

关键词： Visual place recognition domain-invariant information mining module multi-sample joint triplet loss

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FoundationGrasp: Generalizable Task-Oriented Grasping With Foundation Models

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IEEE Transactions on Automation Science and engineering 2025年 22卷 12418-12435页

作者： Tang, Chao Huang, Dehao Dong, Wenlong Xu, Ruinian Zhang, Hong Southern University of Science and Technology Shenzhen Key Laboratory of Robotics and Computer Vision Department of Electronic and Electrical Engineering Shenzhen518055 China Institute for Robotics and Intelligent Machines Georgia Institute of Technology AtlantaGA30332 United States

Task-oriented grasping (TOG), which refers to synthesizing grasps on an object that are configurationally compatible with the downstream manipulation task, is the first milestone towards tool manipulation. Analogous to the activation of two brain regions responsible for semantic and geometric reasoning during cognitive processes, modeling the intricate relationship between objects, tasks, and grasps neces-sitates rich semantic and geometric prior knowledge about these elements. Existing methods typically restrict the prior knowledge to a closed-set scope, limiting their generalization to novel objects and tasks out of the training set. To addresssuch a limitation, we propose FoundationGrasp, a foundationmodel-based TOG framework that leverages the open-ended knowledge from foundation models to learn generalizable TOG skills. Extensive experiments are conducted on the contributed Language and Vision Augmented TaskGrasp (LaViA-TaskGrasp)dataset, demonstrating the superiority of FoundationGrasp over existing methods when generalizing to novel object instances,object classes, and tasks out of the training set. Furthermore,the effectiveness of FoundationGrasp is validated in real-robot grasping and manipulation experiments on a 7-DoF robotic arm. © 2004-2012 IEEE.

关键词： Robotic arms

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Variational Bayesian Adaptive Learning of Deep Latent Variables for Acoustic Knowledge Transfer

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IEEE/ACM Transactions on Audio Speech and Language Processing 2025年 33卷 719-730页

作者： Hu, Hu Siniscalchi, Sabato Marco Yang, Chao-Han Huck Lee, Chin-Hui School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Georgia Institute of Technology University of Palermo Palermo90133 Italy Norwegian University of Science and Technology Trondheim7034 Norway Nvidia Santa ClaraCA95051 United States

In this work, we propose a novel variational Bayesian adaptive learning approach for cross-domain knowledge transfer to address acoustic mismatches between training and testing conditions, such as recording devices and environmental noise. Different from the traditional Bayesian approaches that impose uncertainties on model parameters risking the curse of dimensionality due to the huge number of parameters, we focus on estimating a manageable number of latent variables in deep neural models. Knowledge learned from a source domain is thus encoded in prior distributions of deep latent variables and optimally combined, in a Bayesian sense, with a small set of adaptation data from a target domain to approximate the corresponding posterior distributions. Two different strategies are proposed and investigated to estimate the posterior distributions: Gaussian mean-field variational inference, and empirical Bayes. These strategies address the presence or absence of parallel data in the source and target domains. Furthermore, structural relationship modeling is investigated to enhance the approximation. We evaluated our proposed approaches on two acoustic adaptation tasks: 1) device adaptation for acoustic scene classification, and 2) noise adaptation for spoken command recognition. Experimental results show that the proposed variational Bayesian adaptive learning approach can obtain good improvements on target domain data, and consistently outperforms state-of-the-art knowledge transfer methods. © 2025 IEEE. All rights reserved

关键词： Background noise

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Resonant Chemical Sensor Performance Enhancement through 3D Printed Scaffolds 38

Resonant Chemical Sensor Performance Enhancement through 3D ...

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38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Haile, Biya D. Roeske, Nikolas T. Guo, Hongyu Inan, Omer T. Beardslee, Luke A. Georgia Institute of Technology School of Electrical and Computer Engineering AtlantaGA United States Georgia Institute of Technology Institute for Matter and Systems AtlantaGA United States

ISBN: (纸本)9798331508890

A silicon micromachined gravimetric chemical sensor which is modified with a high surface area 3D-printed polymer coating is presented. The 3D-printed polymer improves both sensor sensitivity and response time compared to spray coated polymers [1]. The sensing film was printed directly on the surface of the hammerhead using three-dimensional (3D) lithography. This demonstrates the ability to generate intricate 3D patterns with exceptional precision within a photoresist devoid of solvents using a UV light-sensitive polymer. Overall, this process leads to an improvement in sensitivity by a factor of 2.5 compared to sensors with spray-coated polymers. © 2025 IEEE.

关键词： Photoresists

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Sub-terahertz transmissive reconfigurable intelligent surface for integrated beam steering and self-OOK-modulation

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Light(Science & Applications) 2025年第1期14卷 131-141页

作者： Dongfang Shen Feng Lan Luyang Wang Tianyang Song Munan Yang Tianyu Hu Yueting Li Xiaolei Nie Jiayao Yang Shixiong Liang Hongxin Zeng Hui-Fang Zhang Pinaki Mazumder Ziqiang Yang Yaxin Zhang Tie Jun Cui Sichuan THz Communication Technology Engineering Research Center School of Electronic Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengdu611731China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou313000China Zhangjiang Laboratory Shanghai201204China School of Microelectronics Tianjin UniversityTianjin300072China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhen518100China Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMI48109USA Southeast University Nanjing210096China

Boasting superior flexibility in beam manipulation and a simpler framework than traditional phased arrays,terahertz metasurface-based phased arrays show great promise for 5G-A/6G communication *** with the reflective reconfigurable intelligent surface(reflective RIS),the transmissive RIS(TRIS)offers more feasibility for transceiver multiplexing systems to meet the growing demand for high-performance beam tracking in terahertz communication and radar ***,the terahertz TRIS encounters greater challenges in phase shift,beam efficiency,and complex ***,we propose a sub-terahertz TRIS based on the phase shift via Pancharatnam-Berry(PB)metasurface and self-on-off keying(OOK)modulation via Schottky *** electrically reconfigurable unit cell consists of a column-wise phase resonator and a rectangular *** experimental retrieved equivalent lumped-element circuit model is implemented in joint field-circuit simulations and is validated by experiments.A fabricated prototype demonstrates excellent performance of TRIS with the minimum insertion loss of 2.8 dB for operational states,large bandwidth nearly covering the entire W-band for 1-bit phase shift,deep OOK amplitude modulation of 12 dB,and wide scanning range of±60°with low specular *** further implement an integrated platform combining high-speed beam steering and spatial-light modulation,verifying the point-to-point signal transmissions in different directions using the TRIS *** proposed TRIS with high-performance and cost-effective fabrication makes it a promising solution to terahertz minimalist communication systems,radar,and satellite communication systems.

关键词： reconfigurable reflective resonator

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A V-Band FMCW Signal Generator With Hybrid Dual-Path VCO Technique Achieving 13.6-GHz Chirp Bandwidth

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IEEE Transactions on Circuits and Systems II: Express Briefs 2025年第5期72卷 658-662页

作者： Chen, Jiangbo Wang, Shengjie Li, Quanyong Zhao, Wenyan Xu, Jingwen Li, Nayu Song, Chunyi Gu, Qun Jane Xu, Zhiwei Institute of Marine Electronic and Intelligent System Ocean College Zhejiang University Zhoushan316021 China Institute of Intelligent Marine Sensing and Communications Donghai Laboratory Zhoushan316021 China Georgia Institute of Technology School of Electrical and Computer Engineering College of Engineering AtlantaGA30332 United States

This brief presents a V-band frequency-modulation continuous wave (FMCW) signal generator for high-resolution radar applications. The proposed hybrid dual-path voltage-controlled oscillator (VCO) employs a digital-assisted capacitance decoding scheme, fully utilizing the tunable capacitance to achieve wideband chirping while maintaining high chirp linearity. To verify the proposed scheme, a radar transceiver with two transmit (TX) channels, and four receive (RX) channels is designed and fabricated in a 65-nm CMOS process. The FMCW signal generator occupies 2.98 mm2 and consumes 120 mW. A measured maximum chirp bandwidth of 13.6 GHz is achieved at TX output with an rms frequency error of 0.008%. The measured phase noise of the VCO is −97.37 dBc/Hz at a 1-MHz offset from a 60-GHz carrier. The proposed FMCW signal generator demonstrates a state-of-the-art chirp bandwidth at V-band. © 2004-2012 IEEE.

关键词： Phase noise

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Use of Simulated Mental Models and Real-time Planning for Human-Robot Interaction

Use of Simulated Mental Models and Real-time Planning for Hu...

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AIAA Science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Swaminathan, Alagappan Ren, Jiming Miller, Haris Kolb, Jack Zhao, Ye Coogan, Samuel Feigh, Karen M. Daniel Guggenheim School of Aerospace Engineering Georgia Institute of Technology AtlantaGA30332 United States George Woodruff School of Mechanical Engineering Georgia Institute of Technology AtlantaGA30332 United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States

ISBN: (纸本)9781624107238

This paper introduces a communication and planning framework to facilitate efficient state update information between an autonomous robotic system and a human operator under scenarios where continuous robotic monitoring is not available. The framework estimates the operator’s mental model and uses the difference between the estimated mental model and the actual world state and robot plans to trigger selective communication updates to the operator. The framework is deployed in a simulation environment where a rapid task planning algorithm adapts robot plans to a dynamic operational environment in real time. The proposed framework aims to improve situational awareness and reduce cognitive load in contrast with baseline methods where communication is triggered by mission milestones, obstacles encountered, or periodically. © 2025, American institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Robot programming

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