检索结果-内蒙古大学图书馆

International Conference on Parallel and Distributed Systems (ICPADS)

作者： Ran Qiu Hu Liang Yuchen Liu Shengrong Zhao Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

Image inpainting, which aims to reconstruct reasonably clear and realistic images from known pixel information, is one of the core problems in computer vision. However, due to the complexity and variability of the underwater environment, the inability to extract valid pixel points and insufficient correlation between feature information in existing image inpainting techniques lead to blurring in the generated images. Therefore, a novel gated attention feature fusion image inpainting network based on generative adversarial networks (GAF-GAN) is proposed. The accuracy of feature similarity matching depends heavily on the validity of the information contained in the features. On the one hand, gating values are dynamically generated by gated convolution to reduce the interference of invalid information. On the other hand, semantic information at distant locations in an image is accurately acquired by the attention mechanism. For these reasons, we designed an improved gated attention mechanism. Gated attention mechanism make the network focus on effective information such as high-frequency texture and color fidelity of restored images. In addition, the dense feature fusion module is added to expand the overall receptive field of the network to fully learn the image features. Experimental results show that the proposed method can effectively repair defective images with complex texture structures and improve the reality and integrity of image details and structures.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Tiered Quadruplet network with Patient-Specific Mining and Dynamic Margin for Improved ugly Duckling Lesion Classification

A Tiered Quadruplet Network with Patient-Specific Mining and...

引用

IEEE International Symposium on Biomedical Imaging

作者： Nathasha Naranpanawa H. Peter Soyer Adam Mothershaw Gayan K. Kulatilleke Zongyuan Ge Brigid Betz-Stablein Shekhar S. Chandra School of Electrical Engineering and Computer Science The University of Queensland Australia Dermatology Research Centre Frazer Institute The University of Queensland Australia Monash Medical AI Monash University Australia Department of Data Science and AI Faculty of IT Monash University Australia

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

The concept of the ‘ugly duckling sign’ is a criterion used in diagnosing cutaneous melanoma by identifying visually distinct skin lesions. However, variations in pigmented lesions among patients make it challenging to visually distinguish ugly ducklings. Hence, we propose DMT-Quadruplet -a deep metric learning network to learn lesion features at two tiers - patient-level and lesion-level. We introduce a patient-specific quadruplet mining approach within a tiered quadruplet network, to capture contextual information both globally and locally. We further incorporate a dynamic margin within the patient-specific mining to allow more useful quadruplets to be mined within individuals. Comprehensive experiments show that our proposed method outperforms traditional classifiers, achieving significantly higher sensitivity than baseline models, successfully classifying ugly duckling lesions both in patient-specific and patient-agnostic contexts.

关键词： Manifolds Learning systems Sensitivity Pipelines Melanoma Feature extraction Extraterrestrial measurements

来源：评论

学校读者我要写书评

暂无评论

LDVNet: Lightweight and Detail-Aware Vision network for Image Recognition Tasks in Resource-Constrained Environments

LDVNet: Lightweight and Detail-Aware Vision Network for Imag...

引用

International Conference on Parallel and Distributed Systems (ICPADS)

作者： Yuchen Liu Hu Liang Ran Qiu Shengrong Zhao Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

In many underwater application scenarios, recognition tasks need to be executed promptly on computationally limited platforms. However, models designed for this field often exhibit spatial locality, and existing works lack the ability to capture crucial details in images. Therefore, a lightweight and detail-aware vision network (LDVNet) for resource-constrained environments is proposed to overcome the limitations of these approaches. Firstly, in order to enhance the accuracy of target image recognition, we introduce transformer modules to acquire global information, thus addressing the issue of spatial locality inherent in traditional convolutional neural networks (CNNs). Secondly, to maintain the network’s lightweight nature, we integrate the transformer module with convolutional operations, thereby mitigating the substantial parameter and floating point operations (FLOPs) overhead. Thirdly, for the efficient extraction of crucial fine-grained details from feature maps, we have devised a channel and spatial attention module (C&SA). This module aids in recognizing intricate and fine-grained visual tasks and enhances image understanding. It is seamlessly integrated into LDVNet with nearly negligible parameter overhead. The experimental results demonstrate that LDVNet outperforms other lightweight networks and hybrid networks in different recognition tasks, while being suitable for resource-constrained environments.

关键词：

来源：评论

学校读者我要写书评

暂无评论

GA-Net: Gated Attention Mechanism Based Global Refinement network for Image Inpainting

GA-Net: Gated Attention Mechanism Based Global Refinement Ne...

引用

International Conference on Parallel and Distributed Systems (ICPADS)

作者： Ran Qiu Shengrong Zhao Hu Liang Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

Underwater images are often affected by problems such as light attenuation, color distortion, noise and scattering, resulting in image defects. A novel image inpainting method is proposed to intelligently predict and fill damaged areas for complete and continuous visualization of the image. First, in order to effectively solve the problem of color distortion caused by light refraction in underwater environments, the improved gated attention mechanism is used. This mechanism improves the local details by learning and weighting the important features of the image. Second, gated convolution automatically determines the degree of restoration for each pixel based on local features of the original image. It eliminates distractions such as low contrast and scattering, retaining more original detailed information. By doing so, image inpainting techniques improve the quality and visualization of underwater images.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Adaptive Neuro-Fuzzy Inference System for Predicting Stock Price of ITMG Issuer

Adaptive Neuro-Fuzzy Inference System for Predicting Stock P...

引用

2021 International Conference on Artificial Intelligence and Big data Analytics, ICAIBDA 2021

作者： Fernanda, Anne Audistya Miliantari, Aprischa Nauva Hidayat, Akik Pravitasari, Anindya Apriliyanti Universitas Padjadjaran Research Center for Artificial Intelligence and Big Data Indonesia Department of Computer Science Faculty of Mathematics and Natural Science Universitas Padjadjaran Sumedang Indonesia Department of Statistics Faculty of Mathematics and Natural Science Universitas Padjadjaran Sumedang Indonesia

ISBN: (纸本)9781665408905

ITMG stock price reflects investor perception of its ability to earn and grow its profits in the future. The prediction is beneficial for determining the movement of the stock price of financial exchange, therefore both issuers and investors could take important steps regarding the financial condition. In this study, a stock price prediction was carried out using the Adaptive Neuro Fuzzy Inference System (ANFIS) method with the Fuzzy Inference System (FIS) Grid Partitioning type. The initial step was to determine the parameters that produce gbellmf as a membership function type, 300 epochs, and a learning rate of 0.03. The calculation of accuracy was carried out using the RMSE calculation. The experiments conducted found that the smallest RMSE calculation result was 0.021942 with 80% of training data. Other issuers can use this method because it can predict stock prices quite well. © 2021 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Deep Perspective Transformation Based Vehicle Localization on Bird’s Eye View

arXiv

引用

arXiv 2023年

作者： Mahyar, Abtin Motamednia, Hossein Rahmati, Dara Department of Computer and Data Sciences Shahid Beheshti University Tehran Iran High Performance Computing Laboratory School of Computer Science Institute for Research in Fundamental Sciences Tehran Iran Faculty of Computer Science and engineering Shahid Beheshti University Tehran Iran

An accurate understanding of a self-driving vehicle’s surrounding environment is crucial for its navigation system. To enhance the effectiveness of existing algorithms and facilitate further research, it is essential to provide comprehensive data to the routing system. Traditional approaches rely on installing multiple sensors to simulate the environment, leading to high costs and complexity. In this paper, we propose an alternative solution by generating a top-down representation of the scene, enabling the extraction of distances and directions of other cars relative to the ego vehicle. We introduce a new synthesized dataset that offers extensive information about the ego vehicle and its environment in each frame, providing valuable resources for similar downstream tasks. Additionally, we present an architecture that transforms perspective view RGB images into bird’s-eye-view maps with segmented surrounding vehicles. This approach offers an efficient and cost-effective method for capturing crucial environmental information for self-driving cars. 1 © 2023, CC BY.

关键词： Birds

来源：评论

学校读者我要写书评

暂无评论

A Secured and Optimized Broadcast Authentication Scheme for the Internet of Medical Things

A Secured and Optimized Broadcast Authentication Scheme for ...

引用

Electrical, computer and Energy Technologies (ICECET), International Conference on

作者： Syed Waleed Riaz Fazlullah Khan Insaf Ullah Bandar Alshawi Ryan Alturki Mohammad Wedyan Computer Science Department Abdul Wali Khan University Mardan KPK Pakistan Faculty of Science and Engineering School of Computer Science University of Nottingham Ningbo China Ningbo Zhejiang China Institute for Analytics and Data Science University of Essex Colchester UK Department of Computer and Network Engineering College of Computing Umm Al-Qura University Makkah Saudi Arabia Department of Software Engineering College of Computing Umm Al-Qura University Makkah Saudi Arabia Department of Computer Sciences Faculty of Information Technology and Computer Sciences Yarmouk University (YU) Irbid Jordan

ISBN: (数字)9798350395914

ISBN: (纸本)9798350395921

This Internet of Medical Things (IoMT), facilitates the medical stop regarding real-time monitoring of patients, medical emergency management, remote surgery, patient information management, medical equipment, drug monitoring, etc. However, IoMT devices communicate with each other in an open environment that makes them vulnerable to a wide range of malicious threats from malicious entities. To protect the devices and their associated data, we designed a broadcast authentication scheme for IoMT devices using identity-based public key cryptography that exploits the lightweight features of the Hyper-Elliptic Curve (HEC). We then performed the security analysis based on the Random Oracle Model (ROM), in which we have proved that the proposed scheme is unforgeable under the hardiness of the hyperelliptic curve discrete logarithm problem. The proposed scheme is analyzed in terms of computational and communication overhead and the experimental results justify the superiority of the proposed work in comparison to the existing schemes.

关键词： Performance evaluation Computational modeling Authentication Surgery Internet of Medical Things Public key cryptography Real-time systems Information management Monitoring Read only memory

来源：评论

学校读者我要写书评

暂无评论

research on long and short-term social recommendation based on convolutional and gated recurrent units

Research on long and short-term social recommendation based ...

引用

International Conference on Parallel and Distributed Systems (ICPADS)

作者： Zihe Jia Peng Xue Zhiqiang Dai Qian Gao Xiaomeng Zhang Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

The development of the Internet has made people more closely related and has put forward higher requirements for recommendation models. Most recommendation models are studied only for the long-term interests of users. In this paper, the interaction time between the user and the item is introduced as auxiliary information in the model construction. Interaction time is used to determine users’ long-term preferences and short-term preferences. In this paper, temporal features are extracted by building a convolutional gated recurrent unit with attention neural network (CNN-GRU-Attention). Firstly, for the problem of accurate feature extraction, CNN are constructed to extract higher-level and more abstract features of themselves and transform high-dimensional data into low-dimensional data; secondly, for the problem of social temporality, GRU are used to not only extract temporal information, but also effectively reduce gradient dispersion, making model convergence and training easier; finally, Graph Attention networks are used to aggregate the social relationship information of users and items respectively, which constitute the final feature representation of users and items respectively. In particular, a modified cosine similarity is used to reduce the error caused by data insensitivity when constructing the social information of the item. In this study, simulation experiments are conducted on two publicly available datasets (Epinions and Ciao), and the experimental results show that the proposed recommended model performs better than other social recommendation models, improving the evaluation metrics of MAE and RMSE by 1.06%-1.33% and 1.19%-1.37%, respectively. The effectiveness of the model innovation is proved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multi-action self-healing coatings with simultaneous recovery of corrosion resistance and adhesion strength

引用

Journal of Materials science & Technology 2022年第6期101卷 18-27页

作者： Chenhao Ren Yao Huang Wenkui Hao Dawei Zhang Xiejing Luo Lingwei Ma Jinke Wang Thee Chowwanonthapunya Chaofang Dong Xiaogang Li Beijing Advanced Innovation Center for Materials Genome Engineering Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China National Materials Corrosion and Protection Data Center University of Science and Technology BeijingBeijing 100083China State Key Laboratory of Advanced Power Transmission Technology(Global Energy Interconnection Research Institute Co.Ltd.) Beijing 100083China Faculty of International Maritime Studies Kasetsart UniversitySriracha Campus199 TungsuklaSrirachaChonburi 20230Thailand BRI Southeast Asia Network for Corrosion and Protection(MOE) Shunde Graduate School of University of Science and Technology BeijingFoshan 528300China

In this study, a new self-healing strategy that can simultaneously recover the corrosion resistance and the adhesion strength of coatings was introduced. The coating was based on a shape memory epoxy resin containing ethylene vinyl acetate(EVA) microspheres loaded with Ce(NO_(3))_(3)inhibitors, and was cured at a relatively high temperature to facilitate the fusion of adjacent microspheres for a strengthened self-healing effect. The electrochemical impedance spectroscopy(EIS) and scanning electrochemical microscopy(SECM) results demonstrated that the shape memory effect of epoxy matrix, the filling of molten EVA microspheres as well as the release of Ce(NO_(3))_(3)inhibitors contributed synergistically to suppress the corrosion reaction at the coating damage. After healing, the low frequency impedance modulus of the coatings containing Ce(NO_(3))_(3)-EVA microspheres was three orders of magnitude higher than that of the blank epoxy coating. The adhesion strength of the coatings containing Ce(NO_(3))_(3)-EVA microspheres on the metal substrate was also largely repaired thanks to the strong bonding effect of the EVA microspheres.

关键词： Self-healing coating Corrosion protection Adhesion strength Shape memory effect Bonding effect

来源：评论

学校读者我要写书评

暂无评论

Transient Session Key Derivation Protocol for Key Escrow Prevention in Public Key Infrastructure 1st

Transient Session Key Derivation Protocol for Key Escrow Pre...

引用

1st EAI International Conference on Internet of Everything, IoECon 2022

作者： Nyangaresi, Vincent Omollo Abduljabbar, Zaid Ameen Maolood, Ismail Yaqub Sibahee, Mustafa A. Al Ma, Junchao Aldarwish, Abdulla J. Y. Faculty of Biological and Physical Sciences Tom Mboya University Homabay40300 Kenya Department of Computer Science College of Education for Pure Sciences University of Basrah Basrah61004 Iraq Shenzhen Institute Huazhong University of Science and Technology Shenzhen518118 China – System Information Ministry of Higher Education and Scientific Research Erbil Iraq College of Big Data and Internet Shenzhen Technology University Shenzhen518118 China Computer Technology Engineering Department Iraq University College Basrah Iraq

ISBN: (纸本)9783031252211

The Internet of Things (IoT) devices have been deployed to realize smart environments such as smart cities, smart homes, smart health and smart grids. In these domains, the IoT devices collect and forward high volumes of sensitive and private data. It is therefore important that security schemes be developed to protect the exchanged data. In this regard, a myriad of authentication protocols have been developed over the recent past. However, these schemes deploy cryptographic primitives that result in extremely high communication, storage and computation complexities. In addition, some of these protocols still have numerous security and privacy issues that render them unsuitable for deployment in an IoT environment. For instance, untraceability, anonymity, key escrow problems and attack vectors such as de-synchronization and forgery attacks are frequently ignored. In this paper, a transient session key derivation protocol is developed to address some of these security and efficiency challenges. The security analysis executed shows that this protocol offers untraceability, device anonymity and perfect forward key secrecy. In addition, it is robust against de-synchronization, known secret key leakage, eavesdropping and forgery attacks. In terms of operational efficiency, this protocol incurs the lowest computation and communication complexities. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Authentication

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：