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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zhongyang Li Xin Yuan Wei Liu Xin Xu School of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Cross-view object geo-localization (CVOGL) aims to locate an object of interest in a captured ground- or drone-view image within the satellite image. However, existing works treat ground-view and drone-view query images equivalently, overlooking their inherent viewpoint discrepancies and the spatial correlation between the query image and the satellite-view reference image. To this end, this paper proposes a novel View-specific Attention Geo-localization method (VAGeo) for accurate CVOGL. Specifically, VAGeo contains two key modules: view-specific positional encoding (VSPE) module and channel-spatial hybrid attention (CSHA) module. In object-level, according to the characteristics of different viewpoints of ground and drone query images, viewpoint-specific positional codings are designed to more accurately identify the click-point object of the query image in the VSPE module. In feature-level, a hybrid attention in the CSHA module is introduced by combining channel attention and spatial attention mechanisms simultaneously for learning discriminative features. Extensive experimental results demonstrate that the proposed VAGeo gains a significant performance improvement, i.e., improving acc@0.25/acc@0.5 on the CVOGL dataset from 45.43%/42.24% to 48.21%/45.22% for ground-view, and from 61.97%/57.66% to 66.19%/61.87% for drone-view.

关键词： Location awareness Accuracy Attention mechanisms Image coding Signal processing Encoding Satellite images Object recognition Speech processing Drones

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A Time Deterministic Dynamic Segmentation Scheduling Algorithm 9

A Time Deterministic Dynamic Segmentation Scheduling Algorit...

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9th IEEE International Conference on Cyber Security and Cloud Computing and 8th IEEE International Conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2022

作者： Gu, Haonan Wu, Jing Guo, Yi Wuhan University of Science and Technology College of Computer Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China

ISBN: (数字)9781665480666

ISBN: (纸本)9781665480666

This paper proposed a soft real-time scheduling algorithm 'time-deterministic dynamic partitioning scheduling' for multimedia tasks in embedded devices. We established a new model based on the characteristics of embedded devices. We developed a pre-scheduling mechanism to select a suitable scheduling strategy based on the actual situation of the task set in the offline cache and to rearrange the task order so as to guarantee the reliability and real-time performance of the system while having higher flexibility and stability. The mechanism also completes the tasks assigned by the system in a stable manner with high utilization. © 2022 IEEE.

关键词： Scheduling algorithms

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Robust tensor decomposition via orientation invariant tubal nuclear norms

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Science China(Technological Sciences) 2022年第6期65卷 1300-1317页

作者： WANG AnDong ZHAO QiBin JIN Zhong LI Chao ZHOU GuoXu School of Automation Guangdong University of TechnologyGuangzhou 510006China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Tensor Learning Team RIKEN Center for Advanced Intelligence ProjectTokyo 103-0027Japan Key Laboratory of Intelligent Perception and System for High-Dimensional Information Ministry of EducationNanjing 210094China Key Laboratory of Intelligent Detection and the Internet of Things in Manufacturing Ministry of EducationGuangzhou 510006China

Aiming at recovering an unknown tensor(i.e.,multi-way array)corrupted by both sparse outliers and dense noises,robust tensor decomposition(RTD)serves as a powerful pre-processing tool for subsequent tasks like classification and target detection in many computer vision and machine learning ***,tubal nuclear norm(TNN)based optimization is proposed with superior performance as compared with other tensorial nuclear norms for tensor ***,one major limitation is its orientation sensitivity due to low-rankness strictly defined along tubal orientation and it cannot simultaneously model spectral low-rankness in multiple *** this end,we introduce two new tensor norms called OITNN-O and OITNN-L to exploit multi-orientational spectral low-rankness for an arbitrary K-way(K≥3)*** further formulate two RTD models via the proposed norms and develop two algorithms as the ***,we establish non-asymptotic error bounds which can predict the scaling behavior of the estimation *** on real-world datasets demonstrate the superiority and effectiveness of the proposed norms.

关键词： tensor recovery t-SVD estimation error tensor completion

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SMWT: A Universal and Lightweight SDN-Based Meter Table Watermarking Traceback Scheme 24

SMWT: A Universal and Lightweight SDN-Based Meter Table Wate...

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24th Asia-Pacific Network Operations and Management Symposium, APNOMS 2023

作者： He, Heng Yang, Sen Zhou, Xiaohu Wang, Jia School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan430081 China Guilin Medical University Guilin541001 China

ISBN: (纸本)9788995004395

The use of anonymous network has increased dramatically due to the development of network technology and people focus on the network security and privacy. However, anonymous networks are often used for illegal purposes, which has caused a significant increase in illegal transactions in the network. Therefore, it is necessary to investigate methods that can trace illegal transactions in anonymous networks. In this paper, we propose a universal and lightweight Software Defined Network (SDN)-based Meter table Watermarking Traceback scheme (SMWT), which is an active watermarking technology. SMWT uses the Bose-Chaudhuri-Hocquenghem (BCH) code as the encoding method and the flow rate as the carrier for the watermark to effectively trace flows of different communication protocols in various anonymous network environments. It utilises the SDN controller to install flow table entries and meter entries to the SDN switch, which can efficiently change the flow rate and embed the watermark in the flow in a stealthily manner. After the flow passes through the anonymous network, the SDN switch can extract the watermark using the flow rate and identify the two communicating parties. We have conducted experiments to evaluate SMWT in a real anonymous network Tor. Compared with other relevant existing schemes, SMWT demonstrated a higher detection rate of 96.7% and a lower false positive rate of 0.3%, as well as high flexibility and stealthiness, low deployment difficulty and controller load. Copyright 2023 KICS.

关键词： Network security

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Research on Crowdsourcing Price Game Model in Crowd Sensing

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computers, Materials & Continua 2021年第8期68卷 1769-1784页

作者： Weijin Jiang Xiaoliang Liu Dejia Shi Junpeng Chen Yongxia Sun Liang Guo School of Computer Science and Technology Hunan University of Technology and BusinessChangsha410205China Key Laboratory of Hunan Province for New Retail Virtual Reality Technology Changsha410205China School of Bioinformatics University of MinnesotaTwin Cities15213USA

Crowd-Sensing is an innovative data acquisition method that combines the perception of mobile devices with the idea of *** is a new application mode under the development of the Internet of *** perceptual data that mobile users can provide is *** crowdsourcing parties will share this limited data,but the cost that the crowdsourcing party can pay is limited,and enough mobile users are needed to complete the perceptual task,making the group wisdom is really *** this process,there is bound to be a game between the crowds and the mobile *** of the existing researches consider a group-aware system.A group of mobile users will directly share or compete for the opportunity of the crowd-holders to do tasks and get paid,the behavior of multiple crowd-source parties,and their bilateral interaction with mobile *** research is not clear enough and there is no targeted *** paper will model and analyze the dynamic evolution process of crowd sensing *** on the unique characteristics of crowd-source non-cooperative game and crowd-sourced Nash equilibrium,we will develop a perceptual plan for mobile users and use the stability analysis of iterative algorithms to explore a way to better match the capabilities of mobile users and the needs of crowdsourced *** theoretical analysis and simulation results verify the dynamic evolution model of crowdsourcing in group perception and propose a method to improve the efficiency of crowdsourcing.

关键词： Crowd-sensing crowdsourcing incentives sensor networks

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Exploring 3D Interaction with Gaze Guidance in Augmented Reality

Exploring 3D Interaction with Gaze Guidance in Augmented Rea...

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IEEE Annual International Symposium virtual Reality

作者： Yiwei Bao Jiaxi Wang Zhimin Wang Feng Lu State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China

Recent research based on hand-eye coordination has shown that gaze could improve object selection and translation experience under certain scenarios in AR. However, several limitations still exist. Specifically, we investigate whether gaze could help object selection with heavy 3D occlusions and help 3D object translation in the depth dimension. In addition, we also investigate the possibility of reducing the gaze calibration burden before use. Therefore, we develop new methods with proper gaze guidance for 3D interaction in AR, and also an implicit online calibration method. We conduct two user studies to evaluate different interaction methods and the results show that our methods not only improve the effectiveness of occluded objects selection but also alleviate the arm fatigue problem significantly in the depth translation task. We also evaluate the proposed implicit online calibration method and find its accuracy comparable to standard 9 points explicit calibration, which makes a step towards practical use in the real world.

关键词： Three-dimensional displays Design methodology Estimation User interfaces Fatigue Calibration Task analysis

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WinDB: HMD-free and Distortion-free Panoptic Video Fixation Learning

arXiv

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arXiv 2023年

作者： Wang, Guotao Chen, Chenglizhao Hao, Aimin Qin, Hong Fan, Deng-Ping The State Key Laboratory of Virtual Reality Technology and Systems Beihang University China The College of Computer Science and Technology China University of Petroleum China The State Key Laboratory of Virtual Reality Technology and Systems Beihang University Research Unit of Virtual Human and Virtual Surgery Chinese Academy of Medical Sciences and with Pengcheng Laboratory China The Computer Science Department Stony Brook University United States ETH Zurich Zurich Switzerland

To date, the widely adopted way to perform fixation collection in panoptic video is based on a head-mounted display (HMD), where users' fixations are collected while wearing an HMD to explore the given panoptic scene freely. However, this widely-used data collection method is insufficient for training deep models to accurately predict which regions in a given panoptic are most important when it contains intermittent salient events. The main reason is that there always exist "blind zooms" when using HMD to collect fixations since the users cannot keep spinning their heads to explore the entire panoptic scene all the time. Consequently, the collected fixations tend to be trapped in some local views, leaving the remaining areas to be the "blind zooms". Therefore, fixation data collected using HMD-based methods that accumulate local views cannot accurately represent the overall global importance - the main purpose of fixations - of complex panoptic scenes. To conquer, this paper introduces the auxiliary window with a dynamic blurring (WinDB) fixation collection approach for panoptic video, which doesn't need HMD and is able to well reflect the regional-wise importance degree. Using our WinDB approach, we have released a new PanopticVideo-300 dataset, containing 300 panoptic clips covering over 225 categories. Specifically, since using WinDB to collect fixations is blind zoom free, there exists frequent and intensive "fixation shifting" - a very special phenomenon that has long been overlooked by the previous research - in our new set. Thus, we present an effective fixation shifting network (FishNet) to conquer it. All these new fixation collection tool, dataset, and network could be very potential to open a new age for fixation-related research and applications in 360o environments. © 2023, CC BY.

关键词： Helmet mounted displays

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Prediction of Geopolymer Concrete Compressive Strength Using Convolutional Neural Networks

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computer Modeling in Engineering & Sciences 2024年第5期139卷 1455-1486页

作者： Kolli Ramujee Pooja Sadula Golla Madhu Sandeep Kautish Abdulaziz S.Almazyad Guojiang Xiong Ali Wagdy Mohamed Department of Civil Engineering VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Information Technology VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Computer Science LBEF Campus(Asia Pacific University of Technology&InnovationMalaysia)Kathmandu44600Nepal Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmmanJordan

Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental *** attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation *** this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering *** achieve this goal,a new approach using convolutional neural networks(CNNs)has been *** study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly *** selection of optimal input parameters is guided by two distinct *** first criterion leverages insights garnered from previous research on the influence of individual features on compressive *** second criterion scrutinizes the impact of these features within the model’s predictive *** to enhancing the CNN model’s performance is the meticulous determination of the optimal *** a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s *** model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score ***,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction *** unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rat

关键词： Class F fly ash compressive strength geopolymer concrete prediction deep learning convolutional neural network

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Deep Learning-based Mortality Prediction of COVID-19 Patients with Cardiovascular Disease

Deep Learning-based Mortality Prediction of COVID-19 Patient...

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IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Huilin Zheng Yingyi Liang Daming Zhang Kai Shi Luxi Dong Xiaolan Xie College of Computer Science and Engineering Guilin University of Technology Guangxi Key Laboratory of Embedded Technology and Intelligent System Guilin University of Technology Guilin China

ISBN: (数字)9798350391367

ISBN: (纸本)9798350391374

Coronavirus disease 2019 (COVID-19) is one of the most dangerous diseases in recorded human history due to its high contagiousness and rapid dissemination. Moreover, people who already have medical issues like cardiovascular disease (CVD) have a higher risk of getting seriously ill. Therefore, this study proposes a deep learning-based prediction model for the mortality of COVID-19 patients with CVD. The research substances are introduced as follows. First, we obtain the original dataset from the Kaggle website provided by the Mexican government, and extract our experimental data. After that, we develop a deep learning-based prediction model for the mortality of COVID-19 patients with CVD while applying a 5-fold cross-validation approach for the model training and validation. Finally, we evaluate the performance of the proposed model and also compare it with many common machine learning models. In our experimental results, the proposed model achieved higher performance than all of the other models. It facilitates decision-making and provides an accurate mortality prediction for COVID-19 patients with CVD.

关键词： COVID-19 Training Support vector machines Radio frequency Government Mortality Machine learning Predictive models Nearest neighbor methods Cardiovascular diseases

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Exploring the usefulness of light field super-resolution for object detection

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The Journal of China Universities of Posts and Telecommunications 2021年第5期28卷 68-81页

作者： Zhang Wenzhe Shi Fan Zhao Meng Chen Shengyong Engineering Research Center of Learning-Based Intelligent System of Ministry of Education Tianjin University of TechnologyTianjin 300384China The Key Laboratory of Computer Vision and System of Ministry of Education Tianjin University of TechnologyTianjin 300384China School of Computer Science and Engineering Tianjin University of TechnologyTianjin 300384China The MOE Key Laboratory of Weak-Light Nonlinear Photonics Nankai UniversityTianjin 300457China

In order to solve the impact of image degradation on object detection, an object detection method based on light field super-resolution(LFSR) is proposed. This method takes LFSR as an image enhancement step to provide high-quality images for object detection without using expensive imaging equipment. To evaluate this method, three types of objects: person, bicycle, and car, are chosen and the results are compared from 5 parts: detected object quantity, mean confidence score, detection results in different scenes, error detection, and detection results from different images sizes and detection speed. Experimental results based on the common object in context(COCO) dataset show that the method incorporated LFSR improves performance of object detection models.

关键词： light-field(LF) super-resolution(SR) object detection RetinaNet YOLOv3 TinyYOLOv3

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