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32nd ACM International Conference on Multimedia, MM 2024

作者： Wu, Zongqian Liu, Yujing Zhan, Mengmeng Hu, Ping Zhu, Xiaofeng School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Guangxi Key Lab of Multisource Information Mining and Security Guangxi Normal University Guilin China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen China

ISBN: (纸本)9798400706868

Although current prompt learning methods have successfully been designed to effectively reuse the large pre-trained models without fine-tuning their large number of parameters, they still have limitations to be addressed, i.e., without considering the adverse impact of meaningless patches in every image and without simultaneously considering in-sample generalization and out-of-sample generalization. In this paper, we propose an adaptive multi-modality prompt learning to address the above issues. To do this, we employ previous text prompt learning and propose a new image prompt learning. The image prompt learning achieves in-sample and out-of-sample generalization, by first masking meaningless patches and then padding them with the learnable parameters and the information from texts. Moreover, each of the prompts provides auxiliary information to each other, further strengthening these two kinds of generalization. Experimental results on real datasets demonstrate that our method outperforms SOTA methods, in terms of different downstream tasks. © 2024 ACM.

关键词： Contrastive Learning

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Fuzzy C-Means Algorithm Based on Density Canopy and Manifold Learning

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Computer systems science & engineering 2024年第3期48卷 645-663页

作者： Jili Chen Hailan Wang Xiaolan Xie Guangxi Key Laboratory of Embedded Technology and Intelligent System Guilin541006China College of Information Science and Engineering Guilin University of TechnologyGuilin541004China

Fuzzy C-Means(FCM)is an effective and widely used clustering algorithm,but there are still some *** the number of clusters must be determined manually,the local optimal solutions is easily influenced by the random selection of initial cluster centers,and the performance of Euclid distance in complex high-dimensional data is *** solve the above problems,the improved FCM clustering algorithm based on density Canopy and Manifold learning(DM-FCM)is ***,a density Canopy algorithm based on improved local density is proposed to automatically deter-mine the number of clusters and initial cluster centers,which improves the self-adaptability and stability of the ***,considering that high-dimensional data often present a nonlinear structure,the manifold learning method is applied to construct a manifold spatial structure,which preserves the global geometric properties of complex high-dimensional data and improves the clustering effect of the algorithm on complex high-dimensional ***-Mallows Index(FMI),the weighted average of homogeneity and completeness(V-measure),Adjusted Mutual information(AMI),and Adjusted Rand Index(ARI)are used as performance measures of clustering *** experimental results show that the manifold learning method is the superior distance measure,and the algorithm improves the clustering accuracy and performs superiorly in the clustering of low-dimensional and complex high-dimensional data.

关键词： Fuzzy C-Means(FCM) cluster center density canopy ISOMAP clustering

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Blockchain-based color medical image cryptosystem for industrial Internet of Healthcare Things (IoHT)

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Multimedia Tools and Applications 2024年 1-55页

作者： Khallaf, Fatma El-Shafai, Walid El-Rabaie, El-Sayed M. El-Samie, Fathi E. Abd Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Electrical Engineering Faculty of Engineering Ahram Canadian University 6th October City Giza Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

In recent years, the proliferation of smart devices and associated technologies, such as the Internet of Things (IoT), Industrial Internet of Things (IIoT), and Internet of Medical Things (IoMT), has witnessed a substantial growth. However, the limited processing power and storage capacity of smart devices make them vulnerable to cyberattacks, rendering traditional security and cryptography techniques inadequate. To address these challenges, blockchain (BC) technology has emerged as a promising solution. This study introduces an efficient framework for the Internet of Healthcare Things (IoHT), presenting a novel cryptosystem for color medical images using BC technology in conjunction with the IoT, Secure Hash Algorithm 256-bit (SHA256), shuffling, and bitwise XOR operations. The encryption scheme is specifically designed for an IIoT grid network computing system, relying on diffusion and confusion principles. In this paper, the proposed cryptosystem strength is evaluated against differential attacks with several comprehensive metrics. Simulation results and theoretical analysis demonstrate the cryptosystem effectiveness, showcasing its ability to provide high levels of security and immunity to data leakage. The proposed cryptosystem offers a versatile range of technical solutions and strategies that are adaptable to various scenarios. The evaluation metrics, with approximate values of 99.61% for Number of Pixels Change Rate (NPCR), 33.46% for Unified Average Changed Intensity (UACI), and 8 for information entropy, closely align with the desired ideal outcomes. Consequently, this paper contributes to the advancement of secure and private systems for medical image encryption based on BC technology, potentially mitigating the risks associated with cyberattacks on smart medical devices. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Blockchain

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Deep-Learning-Assisted Underwater 3D Tactile Tensegrity

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Research 2023年第3期2023卷 683-695页

作者： Peng Xu Jiaxi Zheng Jianhua Liu Xiangyu Liu Xinyu Wang Siyuan Wang Tangzhen Guan Xianping Fu Minyi Xu Guangming Xie Zhong Lin Wang Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems Marine Engineering CollegeDalian Maritime UniversityDalian 116026China School of Information Science and Technology Dalian Maritime UniversityDalian 116026China Intelligent Biomimetic Design Lab College of EngineeringPeking UniversityBeijing 100871China Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of SciencesBeijing 100871China School of Materials Science and Engineering Georgia Institute of TechnologyAtlantaGA 30332-0245USA

The growth of underwater robotic applications in ocean exploration and research has created an urgent need for effective tactile ***,we propose an underwater 3-dimensional tactile tensegrity(U3DTT)based on soft self-powered triboelectric nanogenerators and deep-learning-assisted data *** device can measure and distinguish the magnitude,location,and orientation of perturbations in real time from both flow field and interaction with obstacles and provide collision protection for underwater vehicles *** is enabled by the structure that mimics terrestrial animals’musculoskeletal systems composed of both stiff bones and stretchable ***,when successfully integrated with underwater vehicles,the U3DTT shows advantages of multiple degrees of freedom in its shape modes,an ultrahigh sensitivity,and fast response times with a low cost and *** real-time 3-dimensional pose of the U3DTT has been predicted with an average root-mean-square error of 0.76 in a water pool,indicating that this developed U3DTT is a promising technology in vehicles with tactile feedback.

关键词： underwater tile stiff

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Triggered Mechanism for Strict Feedback systems under Unknown Control Directions 14

Triggered Mechanism for Strict Feedback Systems under Unknow...

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14th Asian Control Conference, ASCC 2024

作者： Liu, Guilong Wu, Hongda Yang, Yongliang Xie, Wei Zhang, Weidong School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Department of Automation Shanghai200240 China

ISBN: (纸本)9789887581598

This paper presents an event-based asymptotic tracking control scheme designed for strict feedback systems with unknown control directions. The control directions directly determine how the controller acts on the system, thus impacting the system's stability and convergence speed. When the control directions are unknown, it presents a significant challenge in controller design. To tackle this issue, the Nussbaum-type gains are introduced. However, this method increases communication overhead. Hence, an event-triggered mechanism is introduced to alleviate this burden. Additionally, to achieve and maintain desired target states, satisfying control requirements and performance demands, this paper improves the event-triggered mechanism to achieve asymptotic tracking. Finally, the feasibility and effectiveness of the proposed design are validated through a simulation example. © 2024 Asian Control Association.

关键词： Feedback

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Optically transparent Millimeter-Wave metasurface for frequency-spatial multiplexed holographic imaging 12

Optically transparent Millimeter-Wave metasurface for freque...

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12th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2024

作者： Zhang, Zhiyun Zhang, Guang Zhou, Yulong Li, Sijia Tian, Jianghao Guo, Zexu Cao, Xiangyu Air Force Engineering University Information and Navigation College Xi'an710077 China Shaanxi Changling Electronic Technology Co. Ltd. Baoji721006 China Pla Naval University of Engineering National Key Laboratory of Science and Technology on Vessel Integrated Power System Wuhan430033 China

ISBN: (纸本)9798350351019

Restricted by the physical properties of materials, most traditional electromagnetic (EM) metasurfaces cannot achieve transparent stealth in visible spectrum. Although some metasurfaces for holography have been designed, there is no standard method for evaluating the advancement of wavefront manipulation, metasurface design, and algorithms. Here, a novel full space control the complex amplitude of a metasurface with optical transparency (OT) is presented in the millimeter-wave (mmWave) band. Through frequency-multiplexing, two distinct holographic images 'HOLO' and 'GRAM' with high quality are designed, achieving signal-to-noise ratios (SNR) of 14.6 dB and 14.4 dB, respectively. The 64 × 64 bi-layered metasurface is composed of glass and PET substrates and three silver mesh layers. By changing the opening size and rotating angle of split rings, phase and amplitude modulations are simultaneously and independently realized at 26.6 GHz and 44.0 GHz. © 2024 IEEE.

关键词： Microwave holography

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DeTrack: In-model Latent Denoising Learning for Visual Object Tracking 38

DeTrack: In-model Latent Denoising Learning for Visual Objec...

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38th Conference on Neural information Processing systems, NeurIPS 2024

作者： Zhou, Xinyu Li, Jinglun Hong, Lingyi Jiang, Kaixun Guo, Pinxue Ge, Weifeng Zhang, Wenqiang Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai China Shanghai Engineering Research Center of AI & Robotics Academy for Engineering and Technology Fudan University Shanghai China

Previous visual object tracking methods employ image-feature regression models or coordinate autoregression models for bounding box prediction. Image-feature regression methods heavily depend on matching results and do not utilize positional prior, while the autoregressive approach can only be trained using bounding boxes available in the training set, potentially resulting in suboptimal performance during testing with unseen data. Inspired by the diffusion model, denoising learning enhances the model's robustness to unseen data. Therefore, We introduce noise to bounding boxes, generating noisy boxes for training, thus enhancing model robustness on testing data. We propose a new paradigm to formulate the visual object tracking problem as a denoising learning process. However, tracking algorithms are usually asked to run in real-time, directly applying the diffusion model to object tracking would severely impair tracking speed. Therefore, we decompose the denoising learning process into every denoising block within a model, not by running the model multiple times, and thus we summarize the proposed paradigm as an in-model latent denoising learning process. Specifically, we propose a denoising Vision Transformer (ViT), which is composed of multiple denoising blocks. In the denoising block, template and search embeddings are projected into every denoising block as conditions. A denoising block is responsible for removing the noise in a predicted bounding box, and multiple stacked denoising blocks cooperate to accomplish the whole denoising process. Subsequently, we utilize image features and trajectory information to refine the denoised bounding box. Besides, we also utilize trajectory memory and visual memory to improve tracking stability. Experimental results validate the effectiveness of our approach, achieving competitive performance on several challenging datasets. The proposed in-model latent denoising tracker achieve real-time speed, rendering denoising learning

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Design and Verification of a Penetration system Used for Constructing the Sampling Channel

Design and Verification of a Penetration System Used for Con...

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2022 International Conference on Mechanical, Aerospace technology and Materials Application, MATMA 2022

作者： Ma, Ruqi Ma, Rulin Sun, Kang Chao, Ma Jiang, Shuiqing Institute of Spacecraft System Engineering CAST Beijing100094 China Beijing Academy of Information Science Technology Beijing10094 China

Based on the analysis of the water ice sampling system design at the lunar permanent shadow region(PSR), a rapid sampling channel construction method based on kinetic energy penetration was proposed, and an engineering prototype of the penetrator system based on the conversion of chemical energy and kinetic energy was developed, which can solve the problem that the subsurface lunar water ice is too difficult to sample quickly due to its significantly enhanced mechanical properties. Based on the mechanical properties boundary of lunar soil water ice, the performance of the engineering prototype was tested and verified. The test results show that the penetrating system developed in this paper can achieve rapid penetration into the lunar soil with uniaxial compressive strength of about 30MPa without consuming power consumption;the penetrating depth can reach 234mm, and the penetrating time is less than 1s. The penetrating system can rapidly construct sampling channels, which can effectively solve the problem of the high-hardness water ice samples located at the subsurface layer of the lunar soil that can be efficiently exposed faced by in-situ water ice sampling in the permanent shadow region. © Published under licence by IOP Publishing Ltd.

关键词： Kinetic energy

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An enhanced genetic algorithm for computation task offloading in MEC scenario

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International Journal of Wireless and Mobile Computing 2023年第2期25卷 118-127页

作者： Zhao, Jiacheng Li, Wenzao Liu, Hantao Yu, Peizhen Li, Hanyun Wen, Zhan School of Communication Engineering Chengdu University of Information Technology Sichuan Chengdu China Chengdu University of Information Technology Sichuan Chengdu China Network and Data Security Key Lab of Sichuan Pro. University of Electronic Science and Technology of China Sichuan Chengdu China Educational Informationisation and Big Data Centre Education Department of Sichuan Province Sichuan Chengdu China

The explosive growth of Internet of Things (IoT) and 5G communication technologies has driven the increasing computing demands for wireless devices. Mobile edge computing in the 5G scenario is a promising solution for energy-efficient and low latency applications. However, due to limited bandwidth, the selection of appropriate computing tasks greatly affects the user experience and system performance. Under the wireless bandwidth constraint, the reasonable choice of offloading objects is an NP-hard problem. The genetic algorithm has a great ability to solve this problem, but the performance of the algorithm varies with different scenarios. This paper proposes a task offloading strategy based on an enhanced genetic algorithm for small-scale computing tasks with an ultra-dense terminal distribution. Numerical experiments show that the convergence speed and optimisation effect of the enhanced genetic algorithm are significantly improved compared to the conventional genetic algorithm. © 2023 Inderscience Enterprises Ltd.

关键词： Genetic algorithms

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Phrase Decoupling Cross-Modal Hierarchical Matching and Progressive Position Correction for Visual Grounding

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IEEE Transactions on Multimedia 2025年

作者： Xie, Minghong Wang, Mengzhao Li, Huafeng Zhang, Yafei Tao, Dapeng Yu, Zhengtao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China Yunnan University FIST LAB School of Information Science and Engineering Kunming650091 China

Visual grounding has attracted wide attention thanks to its broad application in various visual language tasks. Although visual grounding has made significant research progress, existing methods ignore the promotion effect of the association between text and image features at different hierarchies on cross-modal matching. This paper proposes a Phrase Decoupling Cross-Modal Hierarchical Matching and Progressive Position Correction Visual Grounding method. It first generates a mask through decoupled sentence phrases, and a text and image hierarchical matching mechanism is constructed, highlighting the role of association between different hierarchies in cross-modal matching. In addition, a corresponding target object position progressive correction strategy is defined based on the hierarchical matching mechanism to achieve accurate positioning for the target object described in the text. This method can continuously optimize and adjust the bounding box position of the target object as the certainty of the text description of the target object improves. This design explores the association between features at different hierarchies and highlights the role of features related to the target object and its position in target positioning. The proposed method is validated on different datasets through experiments, and its superiority is verified by the performance comparison with the state-of-the-art methods. The source code of the proposed method is available at. © 2025 IEEE.

关键词： Visual languages

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