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检索条件"任意字段=3rd International Informatics and Software Engineering Conference, IISEC 2022"

共 2097 条记录，以下是11-20 订阅

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Design and analysis of GPS satellite-based augmentation system based on low earth orbit constellations 3

Design and analysis of GPS satellite-based augmentation syst...

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2024 3rd international conference on Aerospace and Control engineering, ICoACE 2024

作者： Yang, Jianlei Jin, Zhengzhen Zheng, Shuaiyong Huang, Shiyong Ma, Guoyu Ji, Shiran Key Laboratory of Satellite Navigation System and Equipment Technology Shijiazhuang050081 China The 54 Research Institute China Electronics Technology Group Shijiazhuang050081 China School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China College of Software Tianjin Normal University Tianjin300387 China

Addressing the need for improved GPS accuracy, especially for low-dynamic users, this study introduces a GPS augmentation system employing Low Earth Orbit (LEO) satellites. We detail the principles of satellite navigation and augmentation and simulate the GPS-LEO constellation to analyse its performance in terms of satellite visibility and Position Dilution of Precision (PDOP). The results demonstrate substantial augmentation in navigation accuracy with the integrated system, as verified by UAV flight experiments. The integration of LEO satellites is anticipated to advance global navigation capabilities, with implications for intelligent transportation, logistics, and precision agriculture. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Global positioning system

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Fusing Object Detections to Obtain Geolocated Salient Points Using Aerial Images 17th

Fusing Object Detections to Obtain Geolocated Salient Point...

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17th international conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2024

作者： Rudol, Piotr Wzorek, Mariusz Doherty, Patrick Department of Computer and Information Science Linköping University Linköping Sweden Faculty of Informatics Mahasarakham University Mahasarakham44150 Thailand

ISBN: (纸本)9789819606948

This paper addresses the problem of vision-based object geolocation using Unmanned Aerial Vehicles in Search and Rescue settings. It focuses on the task of automatically and accurately geolocating objects of different classes, focusing on human bodies, to provide a map of the detected objects as salient locations. Such maps can be used by responders to plan rescue operations or by other robotic platforms where geolocation is necessary, such as with delivery of medical supplies. The proposed solution strategy leverages recent developments in the field of Convolutional Neural Networks for vision-based object detection with a method for fusing detections. Occupancy probabilities of locations in the environment containing objects of specific classes, or lack thereof, are also computed. This is achieved by taking advantage of a novel sensor model for fusing vision-based detections using both positive and negative observations. The method is validated in simulation as well as with real field experiments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Research on ant colony deep learning under combinatorial generation 3

Research on ant colony deep learning under combinatorial gen...

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3rd international conference on Algorithms, Network, and Communication Technology, ICANCT 2024

作者： Wei, Yong Computer and Software School Shenzhen Institute of Information Technology Shenzhen China

ISBN: (数字)9781510688902

ISBN: (纸本)9781510688896

Combinatorial generation problems have a wide range of applications, and there have been over ten algorithms since the 1960s. As the combination size expands, it is difficult to find the optimal generating solution through enumeration in practice. If the path is defined as a step in two-dimensional coordinates that can only move in the positive direction of X or Y, each generation of combinatorial problem C(m+n, m) can be seen as a route generated by all paths starting from (0, 0) to (m, n) in two-dimensional coordinates. When there are too many generated solutions to be fully enumerated, ant colony algorithm can be used to simulate the foraging process of ant colonies, continuously exploring each route process, and assigning higher pheromones (weights) to paths with high fitness. Obtain weight information maps for each path through deep learning, enabling the algorithm to remember them. Finally, following the path with high weights can quickly obtain a high fitness route. Grouping is a more complex combinatorial problem, and the famous TTP problem is actually the grouping of course units. The article deduces the geometric model generated by the grouping problem, which is a circuit diagram formed by multiple rectangles connected end-to-end in two-dimensional coordinates. Complex combinatorial generation problems can be solved through ant colony deep learning on basic combinatorial generation geometric models, leaving behind memories. This method is simple, efficient, and feasible. © 2025 SPIE.

关键词： Ant colony optimization

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ICAIW 2022 - Joint Proceedings of the 5th international conference on Applied informatics Workshops: 3rd international Workshop on Applied Artificial Intelligence, WAAI 2022, 4th international Workshop on Applied informatics for Economy, Society, and Development, AIESD 2022, 5th international Workshop on Data engineering and Analytics, WDEA 2022, 1st international Workshop on Intelligent Transportation Systems and Smart Mobility Technology, WITS 2022, 2nd international Workshop on Knowledge Management and Information Technologies, WKMIT 2022 and 1st international Workshop on Systems Modeling, WSSC 2022, co-located with the 5th international conference on Applied informatics, ICAI 2022

ICAIW 2022 - Joint Proceedings of the 5th International Conf...

引用

Joint 5th international conference on Applied informatics Workshops, ICAIW 2022: 3rd international Workshop on Applied Artificial Intelligence, WAAI 2022, 4th international Workshop on Applied informatics for Economy, Society, and Development, AIESD 2022, 5th international Workshop on Data engineering and Analytics, WDEA 2022, 1st international Workshop on Intelligent Transportation Systems and Smart Mobility Technology, WITS 2022, 2nd international Workshop on Knowledge Management and Information Technologies, WKMIT 2022 and 1st international Workshop on Systems Modeling, WSSC 2022

The proceedings contain 24 papers. The topics discussed include: analysis on early dropouts in engineering careers;depression diagnosis using text-based AI methods – a systematic review;satellite orbit prediction using a machine learning approach;bibliometric software: the most commonly used in research;bio-business of polymer derived from cassava waste for the industrial plastic sector;dynamic models to determine external factors and their impact on the shrimp price forecast;how to use Instagram to travel the world? an approach to discovering relevant insights from tourist media content;public safety perception in Ecuador: an approach from social networks over data analytics;relationship between corporate social responsibility, assets and income of companies in Ecuador;retrospective of scientific production on e-democracy;sticky floor and glass ceiling in Ecuador. the evolution of the gender wage gap, 2010-2021;and technical indicator for a better intraday understanding of uptrends or downtrends in the financial markets using volume transactions as a trigger.

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3rd international conference on Innovations in Computer Science and software engineering, ICONICS 2022

3rd International Conference on Innovations in Computer Scie...

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3rd international conference on Innovations in Computer Science and software engineering, ICONICS 2022

ISBN: (纸本)9781665461412

The proceedings contain 28 papers. The topics discussed include: experimentation for decentralized resource-based multi-pool mining in Ethereum blockchain;performance enhancement in agriculture sector based on image processing;frameworks, applications and challenges in streaming big data analytics: a review;prevention and safety strategies for road accidents by using evolutionary algorithms;intrusion detection using deep learning techniques;analyzing applicant’s pre-admission data and predicting applicant’s performance in pre-admission test using data mining techniques;quantum computing and machine learning algorithms - a review;real-time violence detection using deep learning techniques;a study on the e-commerce trends using data analysis;and a systematic review on the motivations of cyber-criminals and their attacking policies.

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ICon EEI 2022 - 3rd international conference on Electrical engineering and informatics: Sustainable engineering for Industrial Revolution 4.0, Proceedings

ICon EEI 2022 - 3rd International Conference on Electrical E...

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3rd international conference on Electrical engineering and informatics, ICon EEI 2022

ISBN: (纸本)9781665454346

The proceedings contain 37 papers. The topics discussed include: hybrid method to identify diabetic retinopathy;acetylene black as counter electrode on monolithic perovskite solar cell;hybrid cooperative spectrum sensing algorithm for cognitive radio networks;applied symbiotic organisms search algorithm to solve economic emission dispatch problems;performance evaluation of intrusion detection system performance for traffic anomaly detection based on active IP reputation rules;analysis of PV module performance and electrical parameters based on different tilt angles;a low complexity signal-to-total variance precoding scheme for downlink multi-stream MU-MIMO systems;a comparative study on machine learning based prediction models for public participation rate in an election voting;numerical study on cavities shape for the hydrothermal performance of microchannel heat sinks with elliptical ribs and secondary channels;and remotely operated rotary inverted pendulum system for online control engineering education.

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ICBASE 2022 - Proceedings of the 2022 3rd international conference on Big Data and Artificial Intelligence and software engineering

ICBASE 2022 - Proceedings of the 2022 3rd International Conf...

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3rd international conference on Big Data and Artificial Intelligence and software engineering, ICBASE 2022

The proceedings contain 39 papers. The topics discussed include: vibration region extraction method of bridge based on ground-based MIMO radar;academic paper knowledge graph, the construction and application;research on test case generation method of airborne software based on NLP;3D dynamic hand gesture recognition with fused RGB and depth images;refined balanced resource allocation based on Kubernetes;visible region enhancement network for occluded pedestrian detection;a hierarchical-based frequent itemset mining method under local differential privacy;similarity-aware attention network for multimodal fake news detection;pedestrian attribute recognition based on multi-scale feature fusion over a larger receptive field and strip pooling;stowaway mining: a selfish mining against strategy;spatiotemporal attention networks for traffic demand prediction;and benefits analysis of Chinese cities on urban networks based on evolutionary games.

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Brain Magnetic Resonance Imaging Segmentation System in MS with Deep Neural Networks

Brain Magnetic Resonance Imaging Segmentation System in MS w...

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18th EAI international conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2024

作者： Adamides, Giorgos Panayides, Andreas Loizou, Christos P. Nicolaou, Andria Pantzaris, Marios Pattichis, Constantinos Department of Computer Science University of Cyprus Nicosia Cyprus 3AE HEALTH LTD Nicosia Cyprus CYENS CoE Nicosia Cyprus Department of Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus School of Molecular Medicine The Cyprus Institute of Neurology and Genetics University of Cyprus Nicosia Cyprus

ISBN: (纸本)9783031855719

Multiple Sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system. Nerves are covered by a layer called myelin, which is responsible for protecting and maintaining their functionality. In the case of MS, the myelin becomes damaged, resulting in the nerves functioning unpredictably. MS is a disease characterized by relapses, which can cause permanent and irreversible damage to the patient's mobility, vision, and sensations, unless appropriate medical treatment is administered in time. This highlights the importance of the early detection of the presence or differentiation of MS using computer assisted diagnosis (CAD) systems. This study proposes an automatic segmentation approach of MS damaged regions using deep neural networks that can be integrated with any 3rd party CAD system. The data utilized comprised of a total of 1838 T2-type Magnetic Resonance Imaging (MRI) images collected from a cohort of 38 patients who underwent imaging at two distinct time points. Each MRI image was accompanied by meta-data, detailing the specific locations of the observed damage attributed to MS. The experimental setup investigated and optimized a comprehensive combination of different data preprocessing and augmentation steps, using several variations of the U-Net convolutional neural network (CNN), like U-Net++, Attention U-Net, ResUNet-a and TransUNet. The proposed methods achieved a segmentation accuracy of 0.70 based on the Dice Similarity Coefficient (DSC), a performance comparable to 2D and 3D state-of-the-art approaches in literature. A software framework encapsulating the automated model was also developed to facilitate the clinical practice workflow and underpin adoption by medical practitioners. © ICST Institute for Computer Sciences, Social informatics and Telecommunications engineering 2025.

关键词： Image segmentation

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Malware-BERT: Enhancing Evasive Malware Detection with Multi-Head BERT Attention with Hybrid BERT models

Malware-BERT: Enhancing Evasive Malware Detection with Multi...

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Disruptive Technologies (ICDT), international conference on

作者： Neha Nandinee Deepak Singh Tomar Yogesh Kumar Sharma Vasudev Dehalwar Department of Computer and Engineering Maulana Azad National Institute of Technology Bhopal India

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

The increasing prevalence of malicious software poses a significant threat to computer systems and the Internet, with some malware employing sophisticated techniques to evade detection. Traditional detection methods, such as signature-based and heuristic-based approaches, often fail to identify unknown malware, underscoring the need for advanced solutions. This research introduces the Malware-BERT model for detecting evasive malware in PDF documents. Leveraging a novel dataset, Evasive-PDFMal2022, which comprises 10,025 samples (5,557 malicious and 4,468 benign), the model utilizes BERT embeddings and multi-head attention mechanisms. A comparative analysis of hybrid BERT models reveals significant improvements in detection performance, with the RoBERTa model achieving an accuracy of 96%. This study demonstrates the potential of advanced machine learning techniques in fortifying cybersecurity measures against sophisticated PDF-based threats.

关键词： Analytical models Attention mechanisms Accuracy Computational modeling Portable document format Feature extraction Malware Internet Computer security Disruptive technologies

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Extending APAL to Detect Overlapping Communities in Weighted Networks 3

Extending APAL to Detect Overlapping Communities in Weighted...

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3rd international informatics and software engineering conference, iisec 2022

作者： Oguz, Kaya Doluca, Osman Izmir University of Economics Department of Computer Engineering Turkey Izmir University of Economics Department of Biomedical Engineering Turkey

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

APAL is an overlapping community detection algorithm that runs on undirected and unweighted graphs of any size. This study extends the algorithm to weighted networks by incorporating the average weight of the community to the evaluation process of the detected communities. Weighted-APAL (WAPAL) is tested with the established LFR benchmark suite against the weighted version of CPM. The resulting normalized mutual information scores show that it can detect weighted communities with a high rate of success. © 2022 IEEE.

关键词： Population dynamics

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