检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image segmentation, featuring a large-scale dataset spanning nine common imaging modalities from over 20 different institutions. The top teams developed lightweight segmentation foundation models and implemented an efficient inference pipeline that substantially reduced computational requirements while maintaining state-of-the-art segmentation accuracy. Moreover, the post-challenge phase advanced the algorithms through the design of performance booster and reproducibility tasks, resulting in improved algorithms and validated reproducibility of the winning solution. Furthermore, the best-performing algorithms have been incorporated into the open-source software with a user-friendly interface to facilitate clinical adoption. The data and code are publicly available to foster the further development of medical image segmentation foundation models and pave the way for impactful real-world applications. © 2024, CC BY-NC-SA.

关键词： Open source software

来源：评论

学校读者我要写书评

暂无评论

CorrDetector: A framework for structural corrosion detection from drone images using ensemble deep learning

arXiv

引用

arXiv 2021年

作者： Mohammad Forkana, Abdur Rahim Kang, Yong-Bin Jayaraman, Prem Prakash Liao, Kewen Kaul, Rohit Morgan, Graham Ranjan, Rajiv Sinha, Samir Department of Computer Science and Software Engineering Swinburne University of Technology MelbourneVIC Australia Department of Media and Communication Swinburne University of Technology MelbourneVIC Australia Discipline of Information Technology Peter Faber Business School Australian Catholic University SydneyNSW Australia Newcastle University Newcastle upon TyneNE1 7RU United Kingdom Robonomics AI York Street SydneyNSW Australia

In this paper, we propose a new technique that applies automated image analysis in the area of structural corrosion monitoring and demonstrate improved efficacy compared to existing approaches. Structural corrosion monitoring is the initial step of the risk-based maintenance philosophy and depends on an engineer’s assessment regarding the risk of building failure balanced against the fiscal cost of maintenance. This introduces the opportunity for human error which is further complicated when restricted to assessment using drone captured images for those areas not reachable by humans due to many background noises. The importance of this problem has promoted an active research community aiming to support the engineer through the use of artificial intelligence (AI) image analysis for corrosion detection. In this paper, we advance this area of research with the development of a framework, CorrDetector. CorrDetector uses a novel ensemble deep learning approach underpinned by convolutional neural networks (CNNs) for structural identification and corrosion feature extraction. We provide an empirical evaluation using real-world images of a complicated structure (e.g. telecommunication tower) captured by drones, a typical scenario for engineers. Our study demonstrates that the ensemble approach of CorrDetector significantly outperforms the state-of-the-art in terms of classification accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Lung Nodule Detection and Classification using Random Forest: A Review 9

Lung Nodule Detection and Classification using Random Forest...

引用

9th IEEE International Conference on Intelligent Computing and information Systems, ICICIS 2019

作者： El-Askary, Nada S. Salem, Mohammed A.-M. Roushdy, Mohamed I. Faculty of Computer and Information Sciences Ain Shams University Computer Science Department Cairo Egypt Faculty of Media Engineering and Technology German University Cairo Egypt Faculty of Computer and Information Sciences Future University in Egypt Egypt

ISBN: (纸本)9781728139951

Lung nodule is an abnormal growth of tissues in the lung that can be an onset for lung cancer. Fast detection for those nodules and classifying them will ensure better chances for treatments. Random Forest (RF) is a powerful machine learning algorithm and a state-of-the-art technology that proved to give rewarding results in helping radiologies diagnosing lung pathologies. The paper presents a survey on recent researches made for lung nodule detection and classification using RF. Wide range of datasets can be used for lung nodule detection are listed. Different models with the used features and their results are discussed in this review. © 2019 IEEE.

关键词： Surveys

来源：评论

学校读者我要写书评

暂无评论

Highly Efficient THz Waves Using Laser Chaos

Highly Efficient THz Waves Using Laser Chaos

引用

International Conference on Infrared and Millimeter Waves

作者： Fumiyoshi Kuwashima Mona Jarrahi Semih Cakmakyapan Osamu Morikawa Takuya Shirao Kazuyuki Iwao Kazuyoshi Kurihara Hideaki Kitahara Takeshi Furuya Kenji Wada Yuki Kawakami Takeshi Moriyasu Makoto Nakajima Masahiko Tani Fukui University of Technology 3-6-1 Gakuen Fukui Japan Electrical and Computer Engineering Department University of California Los Angeles 66-147E Engineering IV 420 Westwood Plaza Los Angeles CA USA Chair of Liberal Arts Japan Coast Guard Academy Wakabacho 5-1 Kure Hiroshima Japan School of Education. University. of Fukui 3-9-1 Bunkyo Fukui Japan Research Center for Development of Far-Infrared Region University of Fukui 3-9-1 Bunkyo Fukui Japan Department of Physics and Electronics Osaka Metropolitan University 1-1 Gakuen-cho Naka-ku Sakai Osaka Japan Department of Electronics and Information Engineering National Institute of Technology (KOSEN) Fukui College Geshi-Cho Sabae Fukui Japan Faculty of Engineering University of Fukui 3-9-1 Bunkyo University of Fukui Fukui-city Fukui Japan Institute of Laser engineering Osaka Univ. 2-6 Yamadaoka Suita Osaka Japan

Efficiency of optical beats in a chaotically oscillating laser diode is confirmed comparing that of free running CW laser using a highly efficient plasmonic photomixer. The great potential of chaotically oscillating l...

关键词：

来源：评论

学校读者我要写书评

暂无评论

AngularGrad: A New Optimization Technique for Angular Convergence of Convolutional Neural Networks

arXiv

引用

arXiv 2021年

作者： Roy, Swalpa Kumar Paoletti, Mercedes E. Haut, Juan M. Dubey, Shiv Ram Kar, Purbayan Plaza, Antonio Chaudhuri, Bidyut B. The Computer Science and Engineering Alipurduar Government Engineering and Management College 736206 India The Hyperspectral Computing Laboratory Department of Technology of Computers and Communications University of Extremadura Cáceres10003 Spain The Computer Vision and Biometrics Lab Indian Institute of Information Technology Prayagraj Uttar Pradesh Allahabad211015 India The Media Analysis Group Sony Research India Private Limited Karnataka Bangalore560103 India The Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata700108 India

Convolutional neural networks (CNNs) are trained using stochastic gradient descent (SGD)-based optimizers. Recently, the adaptive moment estimation (Adam) optimizer has become very popular due to its adaptive momentum, which tackles the dying gradient problem of SGD. Nevertheless, existing optimizers are still unable to exploit the optimization curvature information efficiently. This paper proposes a new AngularGrad optimizer that considers the behavior of the direction/angle of consecutive gradients. This is the first attempt in the literature to exploit the gradient angular information apart from its magnitude. The proposed AngularGrad generates a score to control the step size based on the gradient angular information of previous iterations. Thus, the optimization steps become smoother as a more accurate step size of immediate past gradients is captured through the angular information. Two variants of AngularGrad are developed based on the use of Tangent or Cosine functions for computing the gradient angular information. Theoretically, AngularGrad exhibits the same regret bound as Adam for convergence purposes. Nevertheless, extensive experiments conducted on benchmark data sets against state-of-the-art methods reveal a superior performance of AngularGrad. Source code: https://***/mhaut/AngularGrad. Copyright © 2021, The Authors. All rights reserved.

关键词： Optimization

来源：评论

学校读者我要写书评

暂无评论

Reusable Data Visualization Patterns for Clinical Practice 1st

Reusable Data Visualization Patterns for Clinical Practice

引用

1st International Conference on Systems Modelling and Management, ICSMM 2020

作者： Rabbi, Fazle Wake, Jo Dugstad Nordgreen, Tine Department of Information Science and Media Studies University of Bergen Bergen Norway Department of Computer Technology Electrical Engineering and Science Western Norway University of Applied Sciences Bergen Norway NORCE Norwegian Research Centre Bergen Norway eMeistring Bjørgvin DPS Division of Psychiatry Haukeland University Hospital Bergen Norway Department of Clinical Psychology University of Bergen Bergen Norway

ISBN: (纸本)9783030581664

Among clinical psychologists involved in guided internet-facilitated interventions, there is an overarching need to understand patients symptom development and learn about patients need for treatment support. Data visualizations is a technique for managing enormous amounts of data and extract useful information, and is often used in developing digital tool support for decision-making. Although there exists numerous data visualisation and analytical reasoning techniques available through interactive visual interfaces, it is a challenge to develop visualizations that are relevant and suitable in a healthcare context, and can be used in clinical practice in a meaningful way. For this purpose it is necessary to identify actual needs of healthcare professionals and develop reusable data visualization components according to these needs. In this paper we present a study of decision support needs of psychologists involved in online internet-facilitated cognitive behavioural therapy. Based on these needs, we provide a library of reusable visual components using a model-based approach. The visual components are featured with mechanisms for investigating data using various levels of abstraction and causal analysis. © 2020, Springer Nature Switzerland AG.

关键词： Data visualization

来源：评论

学校读者我要写书评

暂无评论

Correction: AI content detection in the emerging information ecosystem: new obligations for media and tech companies

引用

Ethics and information technology 2024年第4期26卷 1-2页

作者： Knott, Alistair Pedreschi, Dino Jitsuzumi, Toshiya Leavy, Susan Eyers, David Chakraborti, Tapabrata Trotman, Andrew Sundareswaran, Sundar Baeza-Yates, Ricardo Biecek, Przemyslaw Weller, Adrian Teal, Paul D. Basu, Subhadip Haklidir, Mehmet Morini, Virginia Russell, Stuart Bengio, Yoshua Social Media Governance Project Global Partnership on AI Montreal Canada School of Engineering and Computer Science Victoria University of Wellington Wellington New Zealand University of Pisa Pisa Italy Chuo University Tokyo Japan Insight SFI Research Centre for Data Analytics School of Information and Communication University College Dublin Dublin Ireland School of Computing University of Otago Dunedin New Zealand Alan Turing Institute London United Kingdom University College London London United Kingdom Institute for Experiential AI Northeastern University Silicon Valley USA Warsaw University of Technology Warsaw Poland University of Cambridge Cambridge United Kingdom Computer Science and Engineering Department Jadavpur University Kolkata India Artificial Intelligence Institute Tubitak Bilgem Gebze Türkiye Center for Human-Compatible AI UC Berkeley Berkeley USA Mila - Quebec AI Institute Montreal Canada University of Montreal Montreal Canada

来源：评论

学校读者我要写书评

暂无评论

Methodology for creation of labeled image datasets of entrained air voids and aggregates in concrete surfaces using confocal laser scanning microscopy

引用

Advanced engineering Informatics 2025年 67卷

作者： Viktor Kostic Qadeer Khan Daniel Cremers Jithender Timothy Thomas Kränkel Christoph Gehlen TUM School of Engineering and Design Department of Materials Engineering Chair of Materials Science and Testing Centre for Building Materials (cbm) Technical University of Munich Munich 81245 BY Germany TUM School of Computation Information and Technology Computer Vision Group Technical University of Munich Munich 81245 BY Germany Munich Center for Machine Learning Munich 81245 BY Germany

Several strategies using neural network algorithms have been established to automate the process of evaluating parameters regarding the freeze–thaw resistance of hardened concrete from image data. However, the performance of such models is dependent on the quality of the datasets used for training. Hand-labeling concrete image data is challenging, where especially small micro air voids (<300 μ m) can be overlooked. This potentially leads to algorithms that are unable to accurately detect the micro air void content, despite being required by current standards (e.g. DIN EN 480-11). To account for this, a method was developed using confocal laser scanning microscopy and the “Segment Anything” model. Acquiring surface height-data through confocal laser scanning microscopy expendites the labeling process and creates more reliable training data due to the detectability of air voids through height differences. Furthermore, by combining the height-data with RGB-images it was possible to accurately distinguish between air voids, aggregates and cement paste with high repeatability between repeated labeling iterations. Keeping high magnification levels (120-480x) enabled the detection of air voids down to 5 μ m. The framework and dataset presented in this study are fundamental for further development of new neural network based algorithms, specialized for the characterization and evaluation of the freeze–thaw resistance of concrete.

关键词： Concrete Freeze–thaw resistance Air voids Labeling Confocal laser scanning microscopy Segment anything model

来源：评论

学校读者我要写书评

暂无评论

In-situ embedding of isotropic conductive adhesives in FFF: A single-step approach to additively manufactured electronics

引用

Materials & Design 2025年 255卷

作者： Timo Banko Stefan Grünwald Rainer Kronberger Hermann Seitz Faculty of Process Engineering Energy and Mechanical Systems TH Köln—University of Applied Sciences 50679 Cologne Germany Faculty of Information Media and Electrical Engineering TH Köln—University of Applied Sciences 50679 Cologne Germany Chair of Microfluidics Faculty of Mechanical Engineering and Marine Technology University of Rostock 18059 Rostock Germany Department of Life Light and Matter University of Rostock 18059 Rostock Germany

Multimaterial additively manufactured electronics (AME) describes the technology of printing conductive and dielectric materials within a single processing system. Commonly used conductive materials, such as metallic nano particle inks, require a subsequent sintering process. This research introduces a novel approach by embedding an isotropic conductive adhesive (ICA) during the fused filament fabrication (FFF) process, involving the dispensing of an ICA into a printed channel and the subsequent deposition of molten thermoplastic on top. Utilizing the heat of the molten thermoplastic, this approach enables the fabrication of low-resistance conductor paths in a single process step. Employing a full factorial design of experiments (DOE), the process parameters effects on the ICAs conductivity and the thermoplastic temperature profile were investigated. The maximum conductivity of 8.27×10 5 S/m was achieved for the conductor path embedded with a liquefier temperature of 300 °C, an embedding speed of 100 mm/sec, and a deposition height of 300 µm. While liquefier temperature and print speed affect the thermoplastics temperature profile, the deposition height affects the cross-sectional geometry of the conductor path, altering its surface-to-volume ratio. This study successfully demonstrates the in-situ fabrication of low-resistance conductor paths in a single process step by utilizing an ICA.

关键词： 3d-printed electronics (3DPE) Additively manufactured electronics (AME) Isotropic conductive adhesive (ICA) Fused filament fabrication (FFF)

来源：评论

学校读者我要写书评

暂无评论

Exploring Potentials and Challenges of Blockchain-based Public Key Infrastructures

Exploring Potentials and Challenges of Blockchain-based Publ...

引用

IEEE Conference on computer Communications Workshops, INFOCOM Wksps

作者： Thomas Hepp Fabian Spaeh Alexander Schoenhals Philip Ehret Bela Gipp Department of Computer and Information Science University of Konstanz Chair of Media Technology University of Wuppertal

Traditional public key infrastructures (PKIs), in particular, X.509 and PGP, is plagued by security and usability issues. As reoccurring incidents show, these are not only of theoretical nature but allow attackers to inflict severe damage. Emerging blockchain technology allows for advances in this area, facilitating a trustless immutable ledger with fast consensus. There have been numerous proposals for utilization of the blockchain in the area of PKI, either as extensions upon existing methods or independent solutions. In this paper, we first study traditional PKI, then proceed with novel approaches, showing how they can improve upon recent issues. We provide a comprehensive evaluation, finding that independent blockchain-based solutions are preferable in the future, mainly due to their stronger security. However, global adoption of these yet requires advances in blockchain development, e.g., concerning scalability.

关键词： Blockchain Public key Servers Usability Smart contracts

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：