检索结果-内蒙古大学图书馆

Intelligent Computing and Control for Engineering and Business Systems (ICCEBS)

作者： Radhika Baskar Rajat Kumar Dwibedi Makhan Kumbhkar Swati Sah Harshal Patil Firos A Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Aarupadai Veedu Institute of Technology VMRF Chennai India Department of Computer Application Indian Institute of Soybean Research Indore India School of SET Sharda university Greater Noida India Computer Science and Engineering Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune India Department of computer Science and Engineering Rajiv Gandhi University (A Central University) Rono-Hills Doimukh Arunachal Pradesh India

Satellite spatial object detection is crucial for urban planning, environmental monitoring, and catastrophe management. The DETR-DC5 (Data Efficient Transformer with DC5 Backbone) is a cutting-edge object detection model. This study introduces DETR-DC5 framework-based satellite spatial object detection improvements. DETR-DC5's strengths are used to improve feature extraction and post-processing. First, a specific feature augmentation technique extracts richer and more discriminative spatial features to let the model capture subtle object attributes. Second, a semi-supervised learning training technique is used to address the lack of labeled satellite imagery data and improve the model's generalization. A new satellite imagery post-processing refining method uses non-maximum suppression methods. This refinement stage reduces false positives and improves localization, especially in densely populated metropolitan regions and complicated natural surroundings. On benchmark satellite imagery datasets, the suggested methods outperform baseline DETR-DC5 models in spatial object detection. Experimental findings indicate significant improvements in precision, recall, and F1-score, proving the upgrades work. This study uses the DETR-DC5 architecture, targeted feature augmentation, semi-supervised training, and refined post-processing algorithms to recognize spatial objects in satellite data. These techniques have the potential to dramatically improve satellite-based object detection, which has implications for urban planning, environmental monitoring, and disaster response.

关键词：

来源：评论

学校读者我要写书评

暂无评论

ENADPool: The Edge-Node Attention-based Differentiable Pooling for Graph Neural Networks

arXiv

引用

arXiv 2024年

作者： Zhao, Zhehan Bai, Lu Cui, Lixin Li, Ming Wang, Yue Xu, Lixiang Hancock, Edwin R. School of Artificial Intelligence Beijing Normal University Beijing China School of Information Central University of Finance and Economics Beijing China The Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Zhejiang Normal University Jinhua China Department of Computer Science University of York York United Kingdom

Graph Neural Networks (GNNs) are powerful tools for graph classification. One important operation for GNNs is the downsampling or pooling that can learn effective embeddings from the node representations. In this paper, we propose a new hierarchical pooling operation, namely the Edge-Node Attention-based Differentiable Pooling (ENADPool), for GNNs to learn effective graph representations. Unlike the classical hierarchical pooling operation that is based on the unclear node assignment and simply computes the averaged feature over the nodes of each cluster, the proposed ENADPool not only employs a hard clustering strategy to assign each node into an unique cluster, but also compress the node features as well as their edge connectivity strengths into the resulting hierarchical structure based on the attention mechanism after each pooling step. As a result, the proposed ENADPool simultaneously identifies the importance of different nodes within each separated cluster and edges between corresponding clusters, that significantly addresses the shortcomings of the uniform edge-node based structure information aggregation arising in the classical hierarchical pooling operation. Moreover, to mitigate the over-smoothing problem arising in existing GNNs, we propose a Multi-distance GNN (MD-GNN) model associated with the proposed ENADPool operation, allowing the nodes to actively and directly receive the feature information from neighbors at different random walk steps. Experiments demonstrate the effectiveness of the MD-GNN associated with the proposed ENADPool. Copyright © 2024, The Authors. All rights reserved.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Edge Detection of SAR Images Based on Shearlet 7th

Edge Detection of SAR Images Based on Shearlet

引用

7th China High-resolution Earth Observation Conference, CHREOC 2020

作者： Sun, Zengguo Zhao, Guodong Chen, Weirong Damaševičius, Robertas Woźniak, Marcin Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an China School of Computer Science Shaanxi Normal University Xi’an China China Centre for Resources Satellite Data and Application Beijing China Department of Applied Informatics Vytautas Magnus University Kaunas Lithuania Faculty of Applied Mathematics Silesian University of Technology Kaszubska 23 Gliwice44-100 Poland

ISBN: (纸本)9789811657344

Synthetic aperture radar (SAR) has the characteristics of all-weather imaging and is widely used in various fields. However, owe to coherent imaging mechanism, speckle appears in SAR images, which seriously affects the interpretation of images. Due to merits of the strong directional sensitivity and the optimal sparsity, shearlet is used to construct an edge detector for SAR images. The detector firstly converts the constructed even symmetric shearlet into odd symmetry by Hilbert transform, then determines the main direction of the edge according to the odd symmetric shearlet coefficient of the SAR image, and calculates the possibility of edge existence according to both odd and even symmetric shearlet coefficient. Experiments show that, in comparison with the traditional difference-based edge detectors, the proposed edge detector has stronger ability of anti-speckle interference, and can better detect the edge information in SAR images. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Speckle

来源：评论

学校读者我要写书评

暂无评论

Effects of chelating agents on the sol-gel synthesis of nano-zirconia:Comparison of the Pechini and sugar-based methods

引用

International Journal of Minerals,Metallurgy and Materials 2020年第5期27卷 693-702页

作者： Faramarz Kazemi Farzin Arianpour Mahdiar Taheri Ali Saberi Hamid Reza Rezaie Department of Mining and Metallurgy Amirkabir University of TechnologyTehranIran Research and Application Center Kastamonu UniversityKastamonuTurkey College of Engineering and Computer Science The Australian National UniversityCanberraAustralia Materials Processing Faculty of Engineering ScienceUniversity of BayreuthBayreuthGermany School of Metallurgy and Materials Engineering Iran University of Science and TechnologyTehranIran

This study focused on the comparison of the Pechini and sugar-based combustion synthesis methods to produce nano-zirconia. Zirconium hydroxide was utilized as metal precursor and citric acid, sucrose, and fructose were used as chelating agents, followed by calcination at 500, 600, and 700°C in air, respectively. Characterization was conducted by thermal analysis, specific surface area measurement, Fourier transform infrared spectroscopy, X-ray diffraction, and scanning and transmission electron microscopy. When sucrose and citric acid were used as chelating agents during synthesis, mixtures of monoclinic and tetragonal phases were formed after calcination at 600 and 700°C. In the fructose samples, the tetragonal structure was the unique characterized phase. The tetragonal parameters in the fructose samples were determined using the diffraction data and the lattice parameter ratio was proven to increase with the temperature increase. Compared with the citrate and sucrose samples, the largest specific surface area(27 m2·g-1) and smallest particle size(39.1 nm) were obtained for the fructose sample after calcination at 700°C. The study revealed the formation of single-phase stabilized tetragonal zirconia using fructose as chelating agent after calcination at 500°C, and the presence and formation mechanism of stabilized tetragonal phase were also discussed on the basis of the X-ray and electron diffraction studies.

关键词： zirconia nanopowder sol-gel sugar Pechini chelation

来源：评论

学校读者我要写书评

暂无评论

FVC-NET: An Automated Diagnosis of Pulmonary Fibrosis Progression Prediction Using Honeycombing and Deep Learning

引用

Computational Intelligence and Neuroscience 2022年 2022卷 2832400页

作者： Yadav, Anju Saxena, Rahul Kumar, Aayush Walia, Tarandeep Singh Zaguia, Atef Kamal, S. M. Mostafa Manipal University Jaipur Jaipur India School of Computer Application Lovely Professional University Phagwara India Department of Computer Science College of Computers and Information Technology Taif University Taif21944 Saudi Arabia Department of Mathematics Islamic University Kushtia7003 Bangladesh

Pulmonary fibrosis is a severe chronic lung disease that causes irreversible scarring in the tissues of the lungs, which results in the loss of lung capacity. The Forced Vital Capacity (FVC) of the patient is an interesting measure to investigate this disease to have the prognosis of the disease. This paper proposes a deep learning-based FVC-Net architecture to predict the progression of the disease from the patient's computed tomography (CT) scan and the patient's metadata. The input to the model combines the image score generated based on the degree of honeycombing for a patient identified based on segmented lung images and the metadata. This input is then fed to a 3-layer net to obtain the final output. The performance of the proposed FVC-Net model is compared with various contemporary state-of-the-art deep learning-based models, which are available on a cohort from the pulmonary fibrosis progression dataset. The model showcased significant improvement in the performance over other models for modified Laplace Log-Likelihood (-6.64). Finally, the paper concludes with some prospects to be explored in the proposed study. © 2022 Anju Yadav et al.

关键词： Metadata

来源：评论

学校读者我要写书评

暂无评论

Multicast Routing Technique for Augmenting Routing Efficiency in mobile WSN

Multicast Routing Technique for Augmenting Routing Efficienc...

引用

International Conference on Computing Methodologies and Communication (ICCMC)

作者： K. Anand M. Rajkumar Srikanth MS S. Radhika Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai Tamil Nadu India School of Information Technology and Engineering VIT University Vellore Tamil Nadu India Program Specialist TNS India Foundation Bangalore Karnataka India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India

mobile Wireless Sensor Network (MWSN) is an active network completely self-governing from a fixed structure. Also, MWSN has small channel bandwidth, great node movement, and inadequate battery energy. In WSN, flooding raises the reliability regarding successful communication of a packet with greater overhead. The flooding consumes the network's resources quickly, especially in terms of the lifetime of the node and energy, etc. Unicast routing creates an extra overhead and increases energy consumption because unicast routing mainly focuses on only minimum distance. But, multicasting is used when the desired destination is at maximum distance and increases the network's reliability in terms of throughput. This paper's objectives are to develop an efficient and reliable protocol using multicasting and unicasting to overcome the issue of higher overhead due to flooding. Multicast Routing Technique for Augmenting (MRTA) routing efficiency in MWSN is introduced. This method aims to enhance the link stability of the route for raising the route lifetime and diminishing the routing load. This method discovers the stable path from several ways to decline the overhead and delay between the sender and receiver. Simulation results demonstrate that this approach improves the network lifetime increases the throughput, and minimizes the routing load in the MWSN.

关键词： Wireless sensor networks Unicast Receivers Multicast communication Routing Throughput Stability analysis

来源：评论

学校读者我要写书评

暂无评论

TranDRL: A Transformer-Driven Deep Reinforcement Learning Enabled Prescriptive Maintenance Framework

arXiv

引用

arXiv 2023年

作者： Zhao, Yang Yang, Jiaxi Wang, Wenbo Yang, Helin Niyato, Dusit 2 Fusionopolis Way Innovis #08-04 Singapore138634 Singapore Shenzhen Institute for Advanced Study School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Mechanical and Electrical Engineering Yunnan Key Laboratory of Intelligent Control and Application Kunming University of Science and Technology Kunming650050 China Department of Information and Communication Engineering Xiamen University Xiamen361005 China School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore

Industrial systems require reliable predictive maintenance strategies to enhance operational efficiency and reduce downtime. Existing studies rely on heuristic models which may struggle to capture complex temporal dependencies. This paper introduces an integrated framework that leverages the capabilities of the Transformer and Deep Reinforcement Learning (DRL) algorithms to optimize system maintenance actions. Our approach employs the Transformer model to effectively capture complex temporal patterns in IoT sensor data, thus accurately predicting the Remaining Useful Life (RUL) of equipment. Additionally, the DRL component of our framework provides cost-effective and timely maintenance recommendations. Numerous experiments conducted on the NASA C-MPASS dataset demonstrate that our approach has a performance similar to the ground-truth results and could be obviously better than the baseline methods in terms of RUL prediction accuracy as the time cycle increases. Additionally, experimental results demonstrate the effectiveness of optimizing maintenance actions. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Research on Optimization Algorithm of Real Estate Enterprise Value Evaluation Based on BP Neural Network

Research on Optimization Algorithm of Real Estate Enterprise...

引用

International Conference on Smart Technologies For Smart Nation (SmartTechCon)

作者： Niranjanamurthy M S. Surendran S. Saravanan Tulsidas Nakrani Mahaveerakannan R M. R. Arun Department of AI and ML BMS Institute of Technology and Management Avalahalli Bangalore Karnataka India Department of Computer Science and Engineering Tagore Engineering College Chennai Tamil Nadu India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Chennai Tamilnadu India Department of Computer Application Sankalchand Patel College of Engineering Sankalchand Patel University Visnagar Gujarat India Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai Tamilnadu India

Because of its professional skills and expertise, it is able to persuade both the buyer and the selling and make the transaction easier. An optimal design scheme for real estate businesses' worth appraisals is proposed here, and it is based on BPNN (BP neural network). A worth appraisal system is developed by doing an analysis of several worth indicators pertaining to real estate companies, and then the system is optimized with the use of BPNN. In the final step, an analysis of the simulation test is performed. According to the findings of the simulation, the arithmetic has a certain accuracy, which is 8.34% higher than the accuracy of traditional arithmetic. On the premise of ensuring the efficient processing of data in batches and finding the rules therein, reduce the impact of human subjectivity, improve the accuracy and scientificity of real estate appraisal, and provide certain reference for the national and local governments to reasonably regulate house prices, so as to promote the stable operation and healthy development of the real estate market. In doing so, you will be able to promote the growth of the real estate market in a healthy manner.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Analysis of Cyber security Risks and Authentication Systems

An Analysis of Cyber security Risks and Authentication Syste...

引用

International Conference on Computing for Sustainable Global Development (INDIACom)

作者： P. Sampath Vijay Shukla Santosh Kumar Anita Gehlot V. Samatha T. Sampath Kumar School of computing EASA college of Engineering and Technology Coimbatore Department of CSE Institute of technology Greater Noida Department of computer science Lucknow Public College of Professional studies Lucknow Uttar Pradesh Uttaranchal Institute of Technology Uttaranchal Univeristy India Computer Application DKW Govt College for women Nellore Dept of CS&AI SR University Telangana India

This paper presents an analysis of cyber security risks and authentication systems. It provides an overview of the most commonly used authentication systems, their pros and cons, and the potential security risks associated with each one. It then discusses the importance of implementing an effective authentication system, the challenges involved in doing so, and the best practices to ensure a secure system. Finally, the paper concludes with recommendations for organizations to consider when implementing authentication systems. The paper provides an in-depth look at cyber security risks and authentication systems in order to help organizations make informed decisions on how to protect their data.

关键词： Government Authentication Insurance Organizations Security computer crime Best practices

来源：评论

学校读者我要写书评

暂无评论

Adaptive Curriculum Learning for Semi-supervised Segmentation of 3D CT-Scans 28th

Adaptive Curriculum Learning for Semi-supervised Segmentati...

引用

28th International Conference on Neural Information Processing, ICONIP 2021

作者： Nartey, Obed Tettey Yang, Guowu Agyapong, Dorothy Araba Yakoba Wu, JinZhao Sarpong, Asare K. Frempong, Lady Nadia Big Data Research Center School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China The School of Computer Science and Electronic Information Guangxi University Nanning530004 China Biomedical Engineering Program Kwame Nkrumah University of Science and Technology Kumasi Ghana School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China School of Medicine Department of Radiology and Imaging Sciences Emory University 1364 Clitton Rd. AtlantaGA30322 United States

ISBN: (纸本)9783030921842

Semi-supervised learning algorithms make use of both labelled training data and unlabelled data. However, the visual domain gap between these sets poses a challenge which prevents deep learning models from obtaining the results they have achieved most especially in the field of medical imaging. Recently, self-training with deep learning has become a powerful approach to leverage labelled training and unlabelled data. However, a challenge of generating noisy pseudo-labels and placing over-confident labelling belief on incorrect classes leads to deviation from the solution. To solve this challenge, the study investigates a curriculum-styled approach for deep semi-supervised segmentation which relaxes and treats pseudo-labels as continuous hidden variables by developing an adaptive pseudo-label generation strategy to jointly optimized the pseudo-label generation and selection process. A regularization scheme is further proposed to smoothen the probability outputs and sharpen the less represented pseudo-label regions. The proposed method was evaluated on three publicly available computer Tomography (CT) scan benchmarks and extensive experiments on all modules have demonstrated the efficacy of the proposed method. © 2021, Springer Nature Switzerland AG.

关键词： Curricula

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：