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检索条件"任意字段=Proceedings of the 6th International Conference on Algorithms, Computing and Systems"

共 6595 条记录，以下是1491-1500 订阅

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Performance Benchmarking of Visual Human Tracking algorithms for UAVs 22

Performance Benchmarking of Visual Human Tracking Algorithms...

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proceedings of the 26th Pan-Hellenic conference on Informatics

作者： theofanis Kalampokas George Papakostas Vassilios Chatzis Stelios Krinidis MLV Research Group Department of Computer Science International Hellenic University Greece Department of Management Science and Technology International Hellenic University Greece

ISBN: (纸本)9781450398541

With the evolution of robotic systems, unmanned aerial vehicles (UAV) have become a target of interest for domains such as computer vision (CV) and artificial intelligence (AI), contributing to a variety of applications for surveillance, transportation and many more. A very hot topic that is the playground of the proposed benchmark is visual human tracking in images acquired by a camera mounted on a UAV. this target application troubles CV and deep learning (DL) research community in recent years and it has created serious demands for visual tracking algorithms. Some of the most important demands are high performance under hard visual tracking conditions and deployment in edge devices with limited computation resources. these two challenges are the main motivation of the presented paper, where 37 tracking algorithms have been benchmarked in visual object tracking (VOT) images. For each tracking algorithm two metric categories, relative to detection performance and hardware resources consumption, have been considered. the objective of the proposed paper is to highlight the most lightweight and high performance tracking algorithms for usage in UAV based applications.

关键词： Computer Vision UAV Visual Tracking Deep Learning Computational Resources Edge computing

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Multi-aircraft behavior recognition method for airport scene based on ASTERIX data

Multi-aircraft behavior recognition method for airport scene...

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IEEE international conference on Civil Aviation Safety and Information Technology (ICCASIT)

作者： Kai Wang Shengwei Li Heng Yue Lieyang Wu Jing Tan Guoqiang Wang The 2nd Research Institute Civil Aviation Administration of China Chengdu China Operation Control Centre of Beijing Capital International Airport Co. Ltd Beijing China Chengdu Tianfu International Airport Chengdu China Jiangxi Traffic Monitoring Command Center Nanchang Jiangxi China The Civil Aviation Chengdu Information Technology Co. Ltd Chengdu China

ISBN: (数字)9798350389418

ISBN: (纸本)9798350389425

To solve the problem that it is difficult to judge the multiple aircraft behaviors through the corresponding trajectory information, all kinds of which are similar in the airport scene video monitoring system, multi-aircraft behavior recognition method for airport scene based on ASTERIX data is proposed. Firstly, ASTERIX data is used to locate the aircraft in the video by the perspective transformation and the historical trajectory information is used to predict the location of aircraft at the next moment, through which can extract the movement area of each aircraft. Namely, the multi-aircraft behavior recognition task is transformed into multiple single-aircraft behavior recognition tasks. Finally, the behavior recognition is completed by the fusion convolution with multi-time scales method in the movement region of each aircraft. the experiment based on a self-made dataset containing various aircraft behaviors at typical airport shows that the proposed method meets the behavior recognition task of multiple targets in the airport scene video monitoring system.

关键词： Accuracy Target recognition Convolution Surveillance Airports Prediction algorithms Real-time systems Trajectory Safety Aircraft

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IMPACT OF DIGITALIZATION ON FIRMS’ PRODUCTIVITY 22

IMPACT OF DIGITALIZATION ON FIRMS’ PRODUCTIVITY

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proceedings of the 6th international conference on Future Networks & Distributed systems

作者： Zarnigor Akhmadalieva Zulfizar Akhmadalieva Department of World Economy Tashkent State University of Economics Uzbekistan Department of Islamic Economics and Finance International Islamic Academy of Uzbekistan Uzbekistan

ISBN: (纸本)9781450399050

Employing Enterprise Survey data that comprises 1276 firms from four Central Asian countries, this study focuses on the impact of digitalization as well as human capital on firms’ productivity. We have found that digitalization improves firms’ productivity by 44-52 percent on average, statistically significant at 1%. Moreover, analysis shows that the impact is heterogenous, with large and statistically significant effects for firms in retail, nonmetal, and, especially, textile industries. these results imply that digitalization is crucial in improving firms’ productivity and the government could implement policies that encourage and help firms with this regard.

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Car Social Network: Contact a Driver through the License Plate 11

Car Social Network: Contact a Driver Through the License Pla...

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11th IEEE international conference on Intelligent Data Acquisition and Advanced computing systems - Technology and Applications (IDAACS)

作者： Russo, Michele Mirulla, Giovanni Avanzato, Roberta Beritelli, Francesco VICOSYST SRL Viale Odor Pordenone I-95128 Catania Italy Univ Catania DIEEI Viale Andrea Doria 6 I-95125 Catania Italy

ISBN: (纸本)9781665426053

the paper presents an innovative car social network service that allows getting in touch with a driver through his individual identification based on the car license plate. the Car Social Network architecture is based on a unified cloud communication platform that enables the activation of multimedia communication sessions with the car *** application contexts range from road safety to the reduction of noise pollution in cities.

关键词： Smart Road Vehicular Network Smart Cities Social Networking Service Unified Communications

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HealthRecSys 2019 - proceedings of the 4th international Workshop on Health Recommender systems, co-located with the 13th ACM conference on Recommender systems 2019, RecSys 2019

HealthRecSys 2019 - Proceedings of the 4th International Wor...

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4th international Workshop on Health Recommender systems, HealthRecSys 2019

the proceedings contain 6 papers. the topics discussed include: inspiring healthy habits: data science at WW;utilizing collaborative filtering to recommend opportunities for positive affect in daily life;personalized, health-aware recipe recommendation: an ensemble topic modeling based approach;rethinking hearing aids as recommender systems;evolutionary approach for ‘healthy bundle’ wellbeing recommendations;and an evaluation of recommendation algorithms for online recipe portals.

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Semantic Interoperability of Digital Twins: Ontology-based Capability Checking in AAS Modeling Framework

Semantic Interoperability of Digital Twins: Ontology-based C...

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Industrial Cyber-Physical systems (ICPS)

作者： Yining Huang Saadia Dhouib Luis Palacios Medinacelli Jacques Malenfant Université Paris-Saclay CEA List Palaiseau France Laboratoire d'Informatique de Paris 6 (LIP6) CNRS Sorbonne Université Paris France

Industry 4.0 currently prepares a major shift towards extreme flexibility into production lines management. Digital Twins are one of the key enabling technologies for Industry 4.0. However, the interoperability gap among digital representation of Industry 4.0 assets is still one of the obstacles to the development and adoption of digital twins. If the Asset Administration Shell (AAS), the standard proposed to represent the I4.0 components, caters for syntactic interoperability, a more semantic kind of interoperability is deeply needed to develop flexible and adaptable production lines. In our work, we overcome the limitation of current syntactic-only resource matching algorithms by implementing semantic interoperability based on ontologies i.e., by transforming AAS-based plant models into MaRCO (Manufacturing Resource Capability Ontology) instances and then query the expanded ontology to find the needed resources. this article presents this ontology-based approach as the first step towards the design and implementation of an automated I4.0 flexible plant supervision and control system based on model-driven engineering (MDE) within the “Papyrus for Manufacturing” toolset. We show how an MDE approach can aggregate around digital twin modeling tools from the Papyrus platform both I4.0 technologies and AI (Knowledge Representation and Reasoning) tools. Our platform aligns modeling and ontological elements to get the best of both worlds. this method has two main advantages: (1) to provide semantic descriptions for digital twin models, (2) to complement model-driven engineering tools with automated reasoning. this paper showcases this approach through a robotic cell use case.

关键词： Adaptation models Unified modeling language Semantics Production Ontologies Cognition Digital twins

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Leveraging LLMs to eXplain DRL Decisions for Transparent 6G Network Slicing

Leveraging LLMs to eXplain DRL Decisions for Transparent 6G ...

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IEEE conference on Network Softwarization (NetSoft)

作者： Mazene Ameur Bouziane Brik Adlen Ksentini EURECOM Sophia-Antipolis France Computer Science Department College of Computing and Informatics Sharjah University Sharjah UAE

ISBN: (数字)9798350369588

ISBN: (纸本)9798350369595

the emergence of 6G networks heralds a transformative era in network slicing, facilitating tailored service delivery and optimal resource utilization. Despite its promise, network slice optimization heavily relies on Deep Reinforcement Learning (DRL) models, often criticized for their black-box decision-making processes. this paper introduces a novel Composable eXplainable Reinforcement Learning (XRL) framework customized for distributed systems like 6G Network Slicing. the proposed framework leverages Large Language Models (LLMs) and Prompt Engineering techniques to elucidate DRL algorithms’ decision-making mechanisms, with a specific emphasis on user profiles. the latter transforms the inherently opaque nature of DRL into an interpretable textual format accessible not only to eXplainable AI (XAI) experts but also to diverse network slice provider stakeholders, engineers, leaders, and beyond. Experimental results underscore the efficacy of the proposed Composable XRL framework, showcasing substantial improvements in transparency and comprehensibility of DRL decisions within the context of 6G network slicing.

关键词： 6G mobile communication Regulators Network slicing Decision making Closed box Transforms Stakeholders

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Calibration-Free Monocular Distance Estimation Performance Assessment Under Influences of Environmental Conditions

Calibration-Free Monocular Distance Estimation Performance A...

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international conference on Information Technology, Information systems and Electrical Engineering (ICITISEE)

作者： Kittikhun Sirinaksomboon Phatham Loahavilai Toshiaki Kondo School of Information Computer and Communication Technology Sirindhorn International Institute of Technology Thammasat University Pathum-Thani Thailand

Single-camera distance measurement can provide a low-cost and setup-free experience. Several techniques to estimate the distance of the object of interest from a single image require calibration for specific parameters and training for a model when machine learning approaches are implemented. this study introduces the use of a single calibration-free image to generate and evaluate a geometric model with a tilted-oriented object. ArUco fiducial marker is utilized since it can be detected easily using its pre-existing detection software. the perimeter, sum of diagonal lengths, and area of the pattern corners are the features for distance estimation. Our algorithm can determine the distance using only a single image in the training stage, which is considered well-balanced between complexity and accuracy in diverse low-cost, setup-free, or calibration-free applications.

关键词： Training Location awareness Software algorithms Estimation Machine learning Cameras Distance measurement

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proceedings of the 46th international conference on Very Large Data Bases, VLDB December 2019

Proceedings of the 46th International Conference on Very Lar...

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46th international conference on Very Large Data Bases, VLDB 2020

this proceedings contains 12 papers. the proceedings of the VLDB Endowment (PVLDB) provides a high-quality publication service to the data management research community. this conference issue covers the topics which include: database indexing and optimization techniques for new hardware and computing platforms, persistent memory, new database join algorithms in the context of stream and sample-based query processing, graph databases, research work on developing new database technologies that support video query processing using neural networks, and also discuss learning individual fairness measures from data and automatic mining of factual mistakes from Wikipedia, etc. the key terms of this proceedings include persistent memory, LSM-based storage systems, bridging theory, vocabulary querying, canonical hub labeling, optimizing databases, s-t simple path enumeration, video analytics, differential indexing, neural network. © VLDB Endowment.

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Human Activity Recognition with IMU and Vital Signs Feature Fusion 28th

Human Activity Recognition with IMU and Vital Signs Feature ...

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28th international conference on MultiMedia Modeling (MMM)

作者： Xefteris, Vasileios-Rafail Tsanousa, Athina Mavropoulos, thanassis Meditskos, Georgios Vrochidis, Stefanos Kompatsiaris, Ioannis Informat Technol Inst Ctr Res & Technol Hellas 6th Km Charilaou Thermi Thessaloniki 57001 Greece Aristotle Univ Thessaloniki Sch Informat Thessaloniki Greece

ISBN: (纸本)9783030983581;9783030983574

Combining data from different sources into an integrated view is a recent trend taking advantage of the Internet of things (IoT) evolution over the last years. the fusion of different modalities has applications in various fields, including healthcare and security systems. Human activity recognition (HAR) is among the most common applications of a healthcare or eldercare system. Inertial measurement unit (IMU) wearable sensors, like accelerometers and gyroscopes, are often utilized for HAR applications. In this paper, we investigate the performance of wearable IMU sensors along with vital signs sensors for HAR. A massive feature extraction, including both time and frequency domain features and transitional features for the vital signs, along with a feature selection method were performed. the classification algorithms and different early and late fusion methods were applied to a public dataset. Experimental results revealed that both IMU and vital signs achieve reasonable HAR accuracy and Fl-score among all the classes. Feature selection significantly reduced the number of features from both IMU and vital signs features while also improved the classification accuracy. the rest of the early and late level fusion methods also performed better than each modality alone, reaching an accuracy level of up to 95.32%.

关键词： Human activity recognition Wearable sensors Vital signals Sensor fusion Feature selection

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