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arXiv 2023年

作者： Zhu, Yabin Li, Chenglong Wang, Xiao Tang, Jin Huang, Zhixiang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Key Laboratory of Electromagnetic Environmental Sensing of Anhui Higher Education Institutes School of Electronic and Information Engineering Anhui University Hefei230601 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Artificial Intelligence Anhui University Hefei230601 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China

Existing Transformer-based RGBT tracking methods either use cross-attention to fuse the two modalities, or use self-attention and cross-attention to model both modality-specific and modality-sharing information. However, the significant appearance gap between modalities limits the feature representation ability of certain modalities during the fusion process. To address this problem, we propose a novel Progressive Fusion Transformer called ProFormer, which progressively integrates single-modality information into the multimodal representation for robust RGBT tracking. In particular, ProFormer first uses a self-attention module to collaboratively extract the multimodal representation, and then uses two cross-attention modules to interact it with the features of the dual modalities respectively. In this way, the modality-specific information can well be activated in the multimodal representation. Finally, a feed-forward network is used to fuse two interacted multimodal representations for the further enhancement of the final multimodal representation. In addition, existing learning methods of RGBT trackers either fuse multimodal features into one for final classification, or exploit the relationship between unimodal branches and fused branch through a competitive learning strategy. However, they either ignore the learning of single-modality branches or result in one branch failing to be well optimized. To solve these problems, we propose a dynamically guided learning algorithm that adaptively uses well-performing branches to guide the learning of other branches, for enhancing the representation ability of each branch. Extensive experiments demonstrate that our proposed ProFormer sets a new state-of-the-art performance on RGBT210, RGBT234, LasHeR, and VTUAV datasets. In particular, the improvements of ProFormer on the LasHeR dataset are up to +6.2%/+ 4.1% in PR/SR compared with existing best RGBT tracker. Copyright © 2023, The Authors. All rights reserved.

关键词： Learning algorithms

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Robust DOA Estimation Based on Dual Lawson Norm for RIS-Aided Wireless Communication Systems

arXiv

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arXiv 2024年

作者： Yu, Canping Li, Yingsong Li, Liping Huang, Zhixiang Wu, Qingqing de Lamare, Rodrigo C. The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui Hefei230601 China The Department of Electronic Engineering Shanghai Jiao Tong University 200240 China Gávea 22451-900 Brazil The School of Physics Engineering and Technology University of York YorkYO10 5DD United Kingdom

Reconfigurable intelligent surfaces (RIS) can actively perform beamforming and have become a crucial enabler for wireless systems in the future. The direction-of-arrival (DOA) estimates of RIS received signals can help design the reflection control matrix and improve communication quality. In this paper, we design a RIS-assisted system and propose a robust Lawson norm-based multiple-signal-classification (LN-MUSIC) DOA estimation algorithm for impulsive noise environments, which is divided into two parts: first, the non-convex Lawson norm is used as the error criterion along with a regularization constraint to formulate the optimization problem. Then, a Bregman distance based alternating-direction-method-of-multipliers (ADMM) is used to solve the problem and recover the desired signal. The second part is to use the multiple-signal-classification (MUSIC) to find out the DOAs of targets based on their sparsity in the spatial domain. In addition, we also propose a RIS control matrix optimization strategy that requires no channel state information (CSI), which effectively enhances the desired signals and improves the performance of the LN-MUSIC algorithm. A Cramér–Rao-lower-bound (CRLB) of the proposed DOA estimation algorithm is presented and verifies its feasibility. Simulated results show that the proposed robust DOA estimate algorithm based on the Lawson norm can effectively suppress the impact of large outliers caused by impulsive noise on the estimation results, outperforming existing *** Codes - Copyright © 2024, The Authors. All rights reserved.

关键词： Impulse noise

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Belief-selective Propagation Detection for MIMO Systems

arXiv

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arXiv 2022年

作者： Zhou, Wenyue Shen, Yifei Li, Liping Huang, Yongming Zhang, Chuan You, Xiaohu National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211189 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China

Compared to the linear MIMO detectors, the Belief Propagation (BP) detector has shown greater capabilities in achieving near optimal performance and better nature to iteratively cooperate with channel decoders. Aiming at real applications, recent works mainly fall into the category of reducing the complexity by simplified calculations, at the expense of performance sacrifice. However, the complexity is still unsatisfactory with exponentially increasing complexity or required exponentiation operations. Furthermore, due to the inherent loopy structure, the existing BP detectors persistently encounter error floor in high signal-to-noise ratio (SNR) region, which becomes even worse with calculation approximation. This work aims at a revised BP detector, named Belief-selective Propagation (BsP) detector by selectively utilizing the trusted incoming messages with sufficiently large a priori probabilities for updates. Two proposed strategies: symbol-based truncation (ST) and edge-based simplification (ES) squeeze the complexity (orders lower than the Original-BP), while greatly relieving the error floor issue over a wide range of antenna and modulation combinations. For the 16-QAM 8 × 4 MIMO system, the B(1, 1) BsP detector achieves more than 4 dB performance gain (@BER = 10−4) with roughly 4 orders lower complexity than the Original-BP detector. Trade-off between performance and complexity towards different application requirement can be conveniently obtained by configuring the ST and ES parameters. © 2022, CC BY.

关键词： Belief propagation

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Hidden Attractors in a Delayed Memristive Differential System with Fractional Order and Chaos Synchronization

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Journal of Harbin Institute of Technology(New Series) 2020年第1期27卷 67-75页

作者： Dawei Ding Yecui Weng Nian Wang School of Electronics and Information Engineering Anhui UniversityHefei 230601China Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationAnhui UniversityHefei 230601China

As an important research branch,memristor has attracted a range of scholars to study the property of memristive chaotic ***,time⁃delayed systems are considered a significant and newly⁃developing field in modern *** combining memristor and time⁃delay,a delayed memristive differential system with fractional order is proposed in this paper,which can generate hidden ***,we discussed the dynamics of the proposed system where the parameter was set as the bifurcation parameter,and showed that with the increase of the parameter,the system generated rich chaotic phenomena such as bifurcation,chaos,and *** we derived adequate and appropriate stability criteria to guarantee the system to achieve ***,examples were provided to analyze and confirm the influence of parameter a,fractional order q,and time delayτon chaos *** simulation results confirm that the chaotic synchronization is affected by a,q andτ.

关键词： fractional order memristive time⁃delay hidden attractors chaos synchronization

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No-Reference Stereoscopic Image Quality Assessment Based on Binocular Collaboration

SSRN

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SSRN 2024年

作者： Guo, Wenzhong Wang, Hanling Ke, Xiao Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing College of Computer and Data Science Fuzhou University Fujian Fuzhou350116 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou University Fuzhou350116 China

Stereoscopic images usually consist of a left view, a right view, and depth information. Stereoscopic/3D image quality assessment (SIQA) is often more challenging compared to 2D-IQA due to the usual scene differences between left and right views and the complexity of the binocular vision fusion process. To address the problem of quality prediction bias of multi-distortion images, we investigated the visual physiology and the processing of visual information by the primary visual cortex of the human brain and proposed a no-reference stereoscopic image quality evaluation method. The method mainly includes an innovative end-to-end NR-SIQA neural network with a picture patch generation algorithm. The algorithm generates a saliency map by fusing the left and right views and then guides the image cropping in the database based on the saliency map. The proposed models are validated and compared based on publicly available databases. The results show that the model and algorithm together outperform the state-of-the-art NR-SIQA metric in the LIVE 3D database and the WIVC 3D database, and have excellent results in the specific noise metric. The model generalization experiments demonstrate a certain degree of generality of our proposed model. © 2024, The Authors. All rights reserved.

关键词： Database systems

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Emotional Knowledge Self-Distillation in Dialogue

Emotional Knowledge Self-Distillation in Dialogue

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Zhongquan Jian Yancheng Wang Weichao Wu Junfeng Yao Meihong Wang Qingqiang Wu School of Informatics Xiamen University Xiamen China School of Computing and Data Science Xiamen University Malaysia Selangor Malaysia School of Mechanics and Civil Engineering China University of Mining & Technology Beijing China School of Film Xiamen University Xiamen China Xiamen Key Laboratory of Intelligent Storage and Computing School of Informatics Xiamen University Xiamen China Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism Xiamen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Recognizing emotions in dialogues is vital for effective human-computer interaction, yet remains a challenging task in Natural Language processing (NLP). Previous studies in Emotion Recognition in Conversation (ERC) have primarily focused on contextual features, while overlooking the importance of emotional features in emotion recognition. To address this gap, we focus on the role of emotional features in ERC and propose a novel method, Emotional Knowledge Self-Distillation (EmoKSD 1 ), to enhance the model’s emotional sensitivity. In EmoKSD, utterances are enriched with implicit ⟨mask⟩ tokens to represent conveyed emotions, allowing the distillation of emotional knowledge from explicit emotional tokens to implicit ⟨mask⟩ tokens, thereby enhancing the model’s ability to perceive subtle emotions within the dialogue. Through thorough evaluations on two public ERC datasets (i.e., IEMOCAP and MELD) using proposed coarse-grained utterance distillation and fine-grained token distillation techniques, EmoKSD demonstrates superior performance compared to existing methods, highlighting the significance of emotional features in ERC.

关键词： Representation learning Human computer interaction Emotion recognition Sensitivity Speech recognition signal processing Natural language processing Acoustics Speech processing

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A Simple Single-Fed Penta-Band Omnidirectional Antenna with Independent Band Control

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IEEE Transactions on Antennas and Propagation 2025年

作者： Zhou, Changfei Gao, Tianyu Zhang, Ruyue Yu, Dapeng Zhang, Wenyu Li, Yingsong Wong, Hang Dalian University of Technology School of Information and Communication Engineering Dalian116024 China Hubei University of Automotive Technology School of Mathematics Physics and Optoelectronic Engineering Shiyan China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei230601 China City University of Hong Kong The State Key Laboratory of Terahertz and Millimeter Waves Hong Kong

A novel method of designing a penta-band omnidirectional low-profile antenna with independent band control is proposed. Single-band, dual-band, tri-band, quad-band, and penta-band antennas are investigated, respectively. The proposed penta-band antenna consists of a circular patch, three concentric metal pins, and two square metal plates. The evolutionary step of the penta-band antenna is achieved by adding metal rings and a small metal plate above the big ground. Each of the four metal rings is excited at TM01 mode resonance, while the 5th mode is generated by a small loop resonance formed by the small plate, shorting pin, stub, and the outer conductor of the cable. The penta-band antenna has a small volume of π × (0.109λ1.53GHz)2 × 0.053λ1.53GHz. The corresponding impedance bandwidths (IMBWs) of the five operating bands are 4.9%, 9.4%, 9.0%, 4.8%, 5.0%. Compared with other designs, the proposed antennas exhibit more flexible bands by using a simple structure. Meanwhile, the antenna has a stable omnidirectional radiation pattern across the five bands and a compact size. © 1963-2012 IEEE.

关键词： Monopole antennas

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Self-Organizing Coverage Method of Swarm Robots Based on Dynamic Virtual Force

SSRN

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SSRN 2024年

作者： Wang, Qiuzhen Zheng, Yue Zou, Juan Liu, Yuan Jianquan, Ouyang Key Laboratory of Intelligent Computing and Information Processing Ministry of Education School of Computer Science School of Cyberspace Science of Xiangtan University Hunan Province Xiangtan China Faculty of School of Computer Science School of Cyberspace Science of Xiangtan University Xiangtan411105 China

Swarm robots often cover designated areas to complete specific tasks, such as forest firefighting or ocean oil spill cleaning. The robot has the ability for local perception and limitedcommunication with surrounding robots, then it is difficult to cope with coverage tasks indynamic environments. This paper proposes a self-organization algorithm for swarm robotsbased on Dynamic Virtual Force (DVF) to cover the dynamic area. One robot in the swarmcan locally perceive the surrounding robots and dynamically select some adjacent robots togenerate virtual repulsion to control its own movement. The swarm robot can be deployed quicklyand uniformly in unknown areas, while being able to adapt itself to changes in dynamic ***, it can adaptively cover parts of an area with different densities, which are dividedaccording to the needs of the area, and different densities require different numbers of robots tobe assigned. We design several groups of simulation experiments, and the results show that thealgorithm achieves good coverage performance and verifies the effectiveness and superiority ofthe method based on DVF. © 2024, The Authors. All rights reserved.

关键词： Robots

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LP-Gaussians: Learnable Parametric Gaussian Splatting for Efficient Dynamic Reconstruction of Single-View Scenes

LP-Gaussians: Learnable Parametric Gaussian Splatting for Ef...

引用

International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Shaoqi Wu Weixing Xie Youhong Peng Jinwen Li Jiawei Yao Junfeng Yao Center for Digital Media Computing School of Film School of Informatics Xiamen University China National Institute for Data Science in Health and Medicine Xiamen University China Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

With the popularity of short video platforms, the number of single-view videos has increased significantly. Existing NeRF-based methods can reconstruct dynamic scenes in a single-view setting, but slow rendering speed and low rendering quality limit their practical applications. To address these challenges, we propose a fast single-view scenes reconstruction framework based on 3D Gaussian Splatting. Our method uses point clouds obtained with depth priors as the Gaussian initialization and introduces learnable parametric functions to model the time-dependent deformation of Gaussians. The explicit deformation modeling for Gaussians significantly reduces training and rendering time. Furthermore, to improve the rendering quality of challenging areas, we adopt an adaptive sampling strategy to densify Gaussians. For occlusion problems from single-view videos, we design a smooth loss function to restore the color of the occluded areas. Experimental results demonstrate that our method significantly reduces training time, enhances rendering quality, and accelerates rendering speed. Project page: https://***/LPGaussians.

关键词： Training Point cloud compression Deformable models Adaptation models Three-dimensional displays Deformation Streaming media signal processing Rendering (computer graphics) Speech processing

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Ask, attend, attack: an effective decision-based black-box targeted attack for image-to-text models 24

Ask, attend, attack: an effective decision-based black-box t...

引用

Proceedings of the 38th International Conference on Neural Information processing Systems

作者： Qingyuan Zeng Zhenzhong Wang Yiu-ming Cheung Min Jiang Department of Artificial Intelligence Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University Xiamen Fujian P.R. China Department of Computing The Hong Kong Polytechnic University Department of Computer Science Hong Kong Baptist University School of Informatics Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism Xiamen University Xiamen Fujian P.R. China

ISBN: (纸本)9798331314385

While image-to-text models have demonstrated significant advancements in various vision-language tasks, they remain susceptible to adversarial attacks. Existing white-box attacks on image-to-text models require access to the architecture, gradients, and parameters of the target model, resulting in low practicality. Although the recently proposed gray-box attacks have improved practicality, they suffer from semantic loss during the training process, which limits their targeted attack performance. To advance adversarial attacks of image-to-text models, this paper focuses on a challenging scenario: decision-based black-box targeted attacks where the attackers only have access to the final output text and aim to perform targeted attacks. Specifically, we formulate the decision-based black-box targeted attack as a large-scale optimization problem. To efficiently solve the optimization problem, a three-stage process Ask, Attend, Attack, called AAA, is proposed to coordinate with the solver. Ask guides attackers to create target texts that satisfy the specific semantics. Attend identifies the crucial regions of the image for attacking, thus reducing the search space for the subsequent Attack. Attack uses an evolutionary algorithm to attack the crucial regions, where the attacks are semantically related to the target texts of Ask, thus achieving targeted attacks without semantic loss. Experimental results on transformer-based and CNN+RNN-based image-to-text models confirmed the effectiveness of our proposed AAA.

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