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arXiv 2024年

作者： Liu, Wenchao Zhang, Xuhui Ren, Jinke Shen, Yanyan Wang, Shuqiang Yang, Bo Guan, Xinping Cui, Shuguang Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong518055 China Southern University of Science and Technology Guangdong518055 China The Shenzhen Future Network of Intelligence Institute The School of Science and Engineering The Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Guangdong Shenzhen518172 China The Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong518055 China Shenzhen University of Advanced Technology Guangdong518055 China The Department of Automation The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China The School of Science and Engineering The Shenzhen Future Network of Intelligence Institute The Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Guangdong Shenzhen518172 China

With the development of artificial intelligence integrated next-generation communication networks, mobile users (MUs) are increasingly demanding the efficient processing of computation-intensive and latency-sensitive tasks. However, existing mobile computing networks struggle to support the rapidly growing computational needs of the MUs. Fortunately, space-air-ground integrated network (SAGIN) supported mobile edge computing (MEC) is regarded as an effective solution, offering the MUs multi-tier and efficient computing services. In this paper, we consider an SAGIN supported MEC system, where a low Earth orbit satellite and multiple unmanned aerial vehicles (UAVs) are dispatched to provide computing services for MUs. An energy efficiency maximization problem is formulated, with the joint optimization of the MU-UAV association, the UAV trajectory, the task offloading decision, the computing frequency, and the transmission power control. Since the problem is non-convex, we decompose it into four subproblems, and propose an alternating optimization based algorithm to solve it. Simulation results confirm that the proposed algorithm outperforms the benchmarks. Copyright © 2024, The Authors. All rights reserved.

关键词： Resource allocation

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IoT Service Description and Composition Method with Knowledge Graph

Journal of Network Intelligence

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Journal of Network intelligence 2022年第4期7卷 1047-1065页

作者： Tang, Zheng-Yi Liu, Chuan Lian, Zhi-Zhu Wang, Jin-Shui Hossain, Md. Alamgir School of Computer Science and Mathematics Fujian University of Technology Xuefu South Road Fujian Province Fuzhou City350118 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Xiyuangong Road Fujian Province Fuzhou City350121 China Key Laboratory of Hunan Province for Mobile Business Intelligence Hunan University of Technology and Business Yuelu Road Hunan Province Changsha City410205 China Department of Management Hajee Mohammad Danesh Science and Technology University Dinajpur5200 Bangladesh

Service computing techniques have achieved remarkable results in solving the cohesiveness problem of Web applications and are therefore introduced into the IoT do-main to break the trend of inlining IoT systems. However, compared with the traditional Internet, IoT has richer elements and semantic connotations, so the existing service description framework needs to be improved and extended. In this paper, we propose an ontology description framework for IoT services, design corresponding inference rules, and give a storage method for IoT services by integrating the knowledge graph technology for the strongly associated characteristics of IoT services. On this basis, an algorithm for combining IoT services based on graph planning is proposed. The experimental results show that the proposed method in this paper can provide richer entity semantics and ef-fectively improve the efficiency and success rate of IoT service composition. © The Authors.

关键词： Ontology

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Fast and accurate single-image depth estimation on mobile devices, mobile AI 2021 challenge: Report

arXiv

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arXiv 2021年

作者： Ignatov, Andrey Malivenko, Grigory Plowman, David Shukla, Samarth Timofte, Radu Zhang, Ziyu Wang, Yicheng Huang, Zilong Luo, Guozhong Yu, Gang Fu, Bin Wang, Yiran Li, Xingyi Shi, Min Xian, Ke Cao, Zhiguo Du, Jin-Hua Wu, Pei-Lin Ge, Chao Yao, Jiaoyang Tu, Fangwen Li, Bo Yoo, Jung Eun Seo, Kwanggyoon Xu, Jialei Li, Zhenyu Liu, Xianming Jiang, Junjun Chen, Wei-Chi Joya, Shayan Fan, Huanhuan Kang, Zhaobing Li, Ang Feng, Tianpeng Liu, Yang Sheng, Chuannan Yin, Jian Benavides, Fausto T. Computer Vision Lab ETH Zurich Switzerland Ltd AI Witchlabs Switzerland Tencent GY-Lab China Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Nanjing Artificial Intelligence Chip Research Institute of Automation Chinese Academy of Sciences China Black Sesame Technologies Inc. Singapore Singapore Visual Media Lab KAIST Korea Republic of Harbin Institute of Technology China Peng Cheng Laboratory China Multimedia and Computer Vision Laboratory National Cheng Kung University Taiwan Samsung Research UK United Kingdom OPPO Research Institute China ETH Zurich Switzerland

Depth estimation is an important computer vision problem with many practical applications to mobile devices. While many solutions have been proposed for this task, they are usually very computationally expensive and thus are not applicable for on-device inference. To address this problem, we introduce the first Mobile AI challenge, where the target is to develop an end-to-end deep learning-based depth estimation solutions that can demonstrate a nearly real-time performance on smartphones and IoT platforms. For this, the participants were provided with a new large-scale dataset containing RGB-depth image pairs obtained with a dedicated stereo ZED camera producing high-resolution depth maps for objects located at up to 50 meters. The runtime of all models was evaluated on the popular Raspberry Pi 4 platform with a mobile ARM-based Broadcom chipset. The proposed solutions can generate VGA resolution depth maps at up to 10 FPS on the Raspberry Pi 4 while achieving high fidelity results, and are compatible with any Android or Linux-based mobile devices. A detailed description of all models developed in the challenge is provided in this paper. Copyright © 2021, The Authors. All rights reserved.

关键词： Computer operating systems

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Array P systems with parallel rewriting and tables of context-free rules

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Journal of Computational and Theoretical Nanoscience 2016年第6期13卷 3636-3642页

作者： Pan, Linqiang Song, Bosheng Isawasan, Pradeep Subramanian, K.G. School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou Henan450002 China Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei430074 China 32 Jalan Anson Penang10400 Malaysia Department of Mathematics and Computer Science Faculty of Science Liverpool Hope University LiverpoolL16 9JD United Kingdom

The two areas of picture languages and membrane computing were linked by array-rewriting P system in which array objects and context-free array-rewriting rules are used in order to generate picture languages. While rewriting arrays in the array-rewriting P system is in a sequential manner, parallel array P system (PAP) involves rewriting of arrays in the regions in parallel in order to generate picture languages. A variant of PAP, known as tabled array P system (TPAP), uses sets of context-free array-rewriting rules, called tables of rules. Generative power of TPAP in comparison with PAP and certain other kinds of picture array generating mechanisms are investigated. Copyright © 2016 American Scientific Publishers. All rights reserved.

关键词： Context free languages

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FST-Net: Facial Soft Tissue Landmark Localization on 3dMD Scans Using Feature Fusion and Local Coordinate Regression

FST-Net: Facial Soft Tissue Landmark Localization on 3dMD Sc...

引用

IEEE International Symposium on Biomedical Imaging

作者： Zhidong He Han Bao Mingzhang Chen Jiasong Wu Luwei Liu Lotfi Senhadji Huazhong Shu Bin Yan Laboratory of Image Science and Technology Southeast University Nanjing China Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Ministry of Education) Southeast University Nanjing China Department of Orthodontics The Affiliated Stomatological Hospital of Nanjing Medical University Nanjing China Centre de Recherche en Information Biomédicale Sino-Français Rennes France INSERM LTSI-UMR 1099 Univ-Rennes Rennes France

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Landmark localization of facial soft tissue (FST) is a basic step in 3D morphometric analysis of human face. However, there are few studies on landmark localization of 3D scan images based on deep learning. The methods based on 2D images cannot be directly applied due to the non-Euclidean data structure. In this paper, we propose an end-to-end learning framework to automatically localize 28 landmarks on 3dMD scans, called FST-Net. Our method extracts features from texture images and mesh models. New texture mappings for 3dMD scans are generated by projection to fuse texture and structure features. A dual-branch network integrating transformers is applied to predict the landmark heatmaps from coarse to fine. A local coordinate regression module based on probabilistic distance and heatmap predictions is proposed to compute the landmark coordinates. We collect and annotate 297 3dMD face scans from the clinic to evaluate our model. Experiments show that the average localization error of the model is 1.204mm (the clinically acceptable precision range is 1.5 mm), and the correct landmark detection rate equals to 70.89%. Our model outperforms the current state-of-the-art deep learning methods for landmark localization on the mesh model.

关键词： Location awareness Deep learning Heating systems Three-dimensional displays Accuracy Computational modeling Biological tissues

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Nuclear norm regularized coding with local position-patch and nonlocal similarity for face hallucination

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Digital Signal processing 2017年 64卷 107-120页

作者： Guangwei Gao Jian Yang Zhihui Lai Pu Huang Jielin Jiang Hao Gao Dong Yue Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing 210023 PR China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou 350121 PR China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing 210094 PR China College of Computer Science and Software Engineering Shenzhen University Shenzhen 518060 PR China Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology Nanjing 210094 PR China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 PR China

Learning-based face hallucination methods have received much attention and progress in past few decades. Specially, position-patch based approaches have been proposed to replace the probabilistic graph-based or manifold learning-based ones. As opposed to the existing patch based methods, where the input image patch matrix is converted into vectors before combination coefficients calculation, in this paper, we propose to directly use the image matrix based regression model for combination coefficients computation to preserve the essential structural information of the input patch matrix. For each input low-resolution (LR) patch matrix, its combination coefficients over the training image patch matrices at the same position can be computed. Then the corresponding high-resolution (HR) patch matrix can be obtained with the LR training patches replaced by the corresponding HR ones. The nonlocal self-similarities are finally utilized to further improve the hallucination performance. Various experimental results on standard face databases indicate that our proposed method outperforms some state-of-the-art algorithms in terms of both visual quantity and objective metrics.

关键词： Face hallucination Position-patch Matrix based regression Nuclear norm Nonlocal similarity

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FireMatch: A Semi-Supervised Video Fire Detection Network Based on Consistency and Distribution Alignment

arXiv

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arXiv 2023年

作者： Lin, Qinghua Li, Zuoyong Zeng, Kun Fan, Haoyi Li, Wei Zhou, Xiaoguang School of Computer Science and Mathematics Fujian University of Technology Fuzhou350118 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450001 China School of Automation Beijing University of Post and Telecommunications Beijing100876 China School of Economics and Management Minjiang University Fuzhou350121 China

Deep learning techniques have greatly enhanced the performance of fire detection in videos. However, video-based fire detection models heavily rely on labeled data, and the process of data labeling is particularly costly and time-consuming, especially when dealing with videos. Considering the limited quantity of labeled video data, we propose a semi-supervised fire detection model called FireMatch, which is based on consistency regularization and adversarial distribution alignment. Specifically, we first combine consistency regularization with pseudo-label. For unlabeled data, we design video data augmentation to obtain corresponding weakly augmented and strongly augmented samples. The proposed model predicts weakly augmented samples and retains pseudo-label above a threshold, while training on strongly augmented samples to predict these pseudo-labels for learning more robust feature representations. Secondly, we generate video cross-set augmented samples by adversarial distribution alignment to expand the training data and alleviate the decline in classification performance caused by insufficient labeled data. Finally, we introduce a fairness loss to help the model produce diverse predictions for input samples, thereby addressing the issue of high confidence with the non-fire class in fire classification scenarios. The FireMatch achieved an accuracy of 76.92% and 91.81% on two real-world fire datasets, respectively. The experimental results demonstrate that the proposed method outperforms the current state-of-the-art semi-supervised classification methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Fires

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Tiny noise, big mistakes: Adversarial perturbations induce errors in Brain-Computer Interface spellers

arXiv

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arXiv 2020年

作者： Zhang, Xiao Wu, Dongrui Ding, Lieyun Luo, Hanbin Lin, Chin-Teng Jung, Tzyy-Ping Chavarriaga, Ricardo Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Civil Engineering and Mechanics Huazhong University of Science and Technology Wuhan430074 China Centre of Artificial Intelligence Faculty of Engineering and Information Technology University of Technology Sydney Sydney2007 Australia La Jolla CA92093 United States Center for Advanced Neurological Engineering Institute of Engineering in Medicine UCSD La Jolla CA92093 United States ZHAW DataLab Zürich University of Applied Sciences Winterthur8401 Switzerland

An electroencephalogram (EEG) based brain-computer interface (BCI) speller allows a user to input text to a computer by thought. It is particularly useful to severely disabled individuals, e.g., amyotrophic lateral sclerosis patients, who have no other effective means of communication with another person or a computer. Most studies so far focused on making EEG-based BCI spellers faster and more reliable;however, few have considered their security. This study, for the first time, shows that P300 and steady-state visual evoked potential BCI spellers are very vulnerable, i.e., they can be severely attacked by adversarial perturbations, which are too tiny to be noticed when added to EEG signals, but can mislead the spellers to spell anything the attacker wants. The consequence could range from merely user frustration to severe misdiagnosis in clinical applications. We hope our research can attract more attention to the security of EEG-based BCI spellers, and more broadly, EEG-based BCIs, which has received little attention before. Copyright © 2020, The Authors. All rights reserved.

关键词： Electroencephalography

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A nonlinear impulsive control system with impulse time windows and un-fixed coefficient of impulsive intensity

A nonlinear impulsive control system with impulse time windo...

引用

International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Yuming Feng Zitao Wang Xiaoyu Liu Wei Zhang Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology Chongqing Three Gorges University Wanzhou Chongqing China School of Computer Science and Engineering Chongqing Three Gorges University Wanzhou Chongqing China Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Wanzhou Chongqing China School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Wanzhou Chongqing China

ISBN: (数字)9781728158570

ISBN: (纸本)9781728158587

Based on the fact that there always exists error in the impulsive intensity, which leads to the fact that the coefficient is un-fixed, and in the occurrence of the impulses, we propose a new model, which is called nonlinear impulsive control system with impulse time windows and un-fixed coefficient of impulsive intensity. We find sufficient conditions for ensuring its stability by using Lypunov's method. We choose chaotic Lorenz system and Chua's system as numerical examples to show the effectiveness of the results, by employing such method, the systems are controlled.

关键词： Impulsive control system impulse time windows impulsive intensity stability control systems Impulsiveness Pulses Time windows

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Determination of Pattern Recognition Problems based on a Pythagorean Fuzzy Correlation Measure from Statistical Viewpoint

Determination of Pattern Recognition Problems based on a Pyt...

引用

International Workshop on Advanced Computational intelligence (IWACI)

作者： Paul Augustine Ejegwa Yuming Feng Shiping Wen Wei Zhang Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Wanzhou Chongqing China School of Computer Science and Engineering Chongqing Three Gorges University Wanzhou Chongqing China Australian AI Institute University of Technology Sydney Ultimo Australia School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Wanzhou Chongqing China

By considering all the three parameters describing Pythagorean fuzzy set, we introduce a new technique of computing correlation coefficient between Pythagorean fuzzy sets from statistical perspective. The correlation coefficient value obtain via this technique shows strength of correlation between the Pythagorean fuzzy sets and indicates whether the Pythagorean fuzzy sets under consideration are related negatively or positively in contrast to other existing correlation coefficient approaches in Pythagorean fuzzy context, which only assess the strength of relationship. Certain numerical examples are considered to ascertain the authenticity of this method over similar techniques studied in intuitionistic/Pythagorean fuzzy contexts. Some pattern recognition problems are resolved with the aid of the new technique. For higher productivity sake, this technique could be approached from an object-oriented perspective.

关键词： Correlation coefficient Productivity Fuzzy sets Correlation Uncertainty Pattern recognition Performance analysis

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