检索结果-内蒙古大学图书馆

Automatic reconstruction of fully volumetric 3D building models from point clouds

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Ochmann, Sebastian Vock, Richard Klein, Reinhard University of Bonn Institute of Computer Science II Endenicher Allee 19a Bonn53115 Germany

We present a novel method for reconstructing parametric, volumetric, multi-story building models from unstructured, unfiltered indoor point clouds by means of solving an integer linear optimization problem. Our approach overcomes limitations of previous methods in several ways: First, we drop assumptions about the input data such as the availability of separate scans as an initial room segmentation. Instead, a fully automatic room segmentation and outlier removal is performed on the unstructured point clouds. Second, restricting the solution space of our optimization approach to arrangements of volumetric wall entities representing the structure of a building enforces a consistent model of volumetric, interconnected walls fitted to the observed data instead of unconnected, paper-thin surfaces. Third, we formulate the optimization as an integer linear programming problem which allows for an exact solution instead of the approximations achieved with most previous techniques. Lastly, our optimization approach is designed to incorporate hard constraints which were difficult or even impossible to integrate before. We evaluate and demonstrate the capabilities of our proposed approach on a variety of complex real-world point clouds. Copyright © 2019, The Authors. All rights reserved.

关键词： Walls (structural partitions)

Ortho-unit polygons can be guarded with at most ⌊n−84 ⌋ guards

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Díaz-Báñez, J.M. Horn, P. Lopez, M.A. Marín, N. Ramírez-Vigueras, A. Solé-Pi, O. Stevens, A. Urrutia, J. Departamento de Matemática Aplicada II Universidad de Sevilla Spain Department of Mathematics University of Denver United States Department of Computer Science University of Denver United States Departamento de Ciencias de la Computación Centro de Investigación Científica y de Educación Superior de Ensenada Baja California Mexico Instituto de Matemáticas UNAM Mexico Department of Mathematics Massachusetts Institute of Technology United States Instituto de Matemáticas Universidad Nacional Autónoma de México Mexico

An orthogonal polygon is called an ortho-unit polygon if its vertices have integer coordinates, and all of its edges have length one. In this paper we prove that any ortho-unit polygon with n ≥ 12 vertices can be gua... 详细信息

关键词： Geometry

Autonomous Artificial Intelligence Agents for Clinical Decision Making in Oncology

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Ferber, Dyke El Nahhas, Omar S.M. Wölflein, Georg Wiest, Isabella C. Clusmann, Jan Leßman, Marie-Elisabeth Foersch, Sebastian Lammert, Jacqueline Tschochohei, Maximilian Jäger, Dirk Salto-Tellez, Manuel Schultz, Nikolaus Truhn, Daniel Kather, Jakob Nikolas Heidelberg University Hospital Heidelberg Germany Else Kroener Fresenius Center for Digital Health Technical University Dresden Dresden Germany School of Computer Science University of St Andrews St Andrews United Kingdom Department of Medicine II Medical Faculty Mannheim Heidelberg University Mannheim Germany Department of Medicine III University Hospital RWTH Aachen Aachen Germany Department of Medicine I University Hospital Dresden Dresden Germany Institute of Pathology University Medical Center Mainz Mainz Germany Munich Germany Munich Germany partner site Munich Germany Initiative partner site Munich Germany Google Cloud Munich Germany Integrated Pathology Unit Institute for Cancer Research Royal Marsden Hospital London United Kingdom Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New YorkNY10065 United States Department of Diagnostic and Interventional Radiology University Hospital Aachen Germany

Multimodal artificial intelligence (AI) systems have the potential to enhance clinical decision-making by interpreting various types of medical data. However, the effectiveness of these models across all medical fields is uncertain. Each discipline presents unique challenges that need to be addressed for optimal performance. This complexity is further increased when attempting to integrate different fields into a single model. Here, we introduce an alternative approach to multimodal medical AI that utilizes the generalist capabilities of a large language model (LLM) as a central reasoning engine. This engine autonomously coordinates and deploys a set of specialized medical AI tools. These tools include text, radiology and histopathology image interpretation, genomic data processing, web searches, and document retrieval from medical guidelines. We validate our system across a series of clinical oncology scenarios that closely resemble typical patient care workflows. We show that the system has a high capability in employing appropriate tools (97%), drawing correct conclusions (93.6%), and providing complete (94%), and helpful (89.2%) recommendations for individual patient cases while consistently referencing relevant literature (82.5%) upon instruction. This work provides evidence that LLMs can effectively plan and execute domain-specific models to retrieve or synthesize new information when used as autonomous agents. This enables them to function as specialist, patient-tailored clinical assistants. It also simplifies regulatory compliance by allowing each component tool to be individually validated and approved. We believe, that our work can serve as a proof-of-concept for more advanced LLM-agents in the medical domain. © 2024, CC BY-NC-ND.

关键词： Autonomous agents

Augmenting the fine beam tube: From hybrid measurements to magnetic field visualization

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Bodensiek, O. Sonntag, D. Wendorff, N. Albuquerque, G. Magnor, M. Institute for Science Education Research Physics Group Technische Universität Braunschweig Computer Graphics Lab Technische Universität Braunschweig

This article may be downloaded for personal use only. Any other use requires permission of the author and AIP Publishing. The following article will appear in The Physics Teacher 57 (2019). Copyright © 2019, The ...

关键词：

Deep learning - A first meta-survey of selected reviews across scientific disciplines, their commonalities, challenges and research impact

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Egger, Jan Pepe, Antonio Gsaxner, Christina Jin, Yuan Li, Jianning Kern, Roman Institute of Computer Graphics and Vision Faculty of Computer Science and Biomedical Engineering Graz University of Technology Graz Austria Computer Algorithms for Medicine Laboratory Graz Austria Department of Oral and Maxillofacial Surgery Medical University of Graz Graz Austria University Medicine Essen Essen Germany Research Center for Connected Healthcare Big Data Zhejiang Lab Zhejiang Hangzhou China Research Unit Experimental Neurotraumatology Department of Neurosurgery Medical University of Graz Graz Austria Knowledge Discovery Know-Center Graz Austria Institute of Interactive Systems and Data Science Graz University of Technology Graz Austria

Deep learning belongs to the field of artificial intelligence, where machines perform tasks that typically require some kind of human intelligence. Deep learning tries to achieve this by drawing inspiration from the learning of a human brain. Similar to the basic structure of a brain, which consists of (billions of) neurons and connections between them, a deep learning algorithm consists of an artificial neural network, which resembles the biological brain structure. Mimicking the learning process of humans with their senses, deep learning networks are fed with (sensory) data, like texts, images, videos or sounds. These networks outperform the state-of-the-art methods in different tasks and, because of this, the whole field saw an exponential growth during the last years. This growth resulted in way over 10,000 publications per year in the last years. For example, the search engine PubMed alone, which covers only a sub-set of all publications in the medical field, provides already over 11,000 results in Q3 2020 for the search term 'deep learning', and around 90% of these results are from the last three years. Consequently, a complete overview over the field of deep learning is already impossible to obtain and, in the near future, it will potentially become difficult to obtain an overview over a subfield. However, there are several review articles about deep learning, which are focused on specific scientific fields or applications, for example deep learning advances in computer vision or in specific tasks like object detection. With these surveys as a foundation, the aim of this contribution is to provide a first high-level, categorized meta-survey of selected reviews on deep learning across different scientific disciplines and outline the research impact that they already have during a short period of time. The categories (computer vision, language processing, medical informatics and additional works) have been chosen according to the underlying data sources (image,

关键词： Surveys

MFR 2021: Masked Face Recognition Competition

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Boutros, Fadi Damer, Naser Kolf, Jan Niklas Raja, Kiran Kirchbuchner, Florian Ramachandra, Raghavendra Kuijper, Arjan Fang, Pengcheng Zhang, Chao Wang, Fei Montero, David Aginako, Naiara Sierra, Basilio Nieto, Marcos Erakın, Mustafa Ekrem Demir, Ugur Ekenel, Hazım Kemal Kataoka, Asaki Ichikawa, Kohei Kubo, Shizuma Zhang, Jie He, Mingjie Han, Dan Shan, Shiguang Grm, Klemen Štruc, Vitomir Seneviratne, Sachith Kasthuriarachchi, Nuran Rasnayaka, Sanka Neto, Pedro C. Sequeira, Ana F. Pinto, Joao Ribeiro Saffari, Mohsen Cardoso, Jaime S. Fraunhofer Institute for Computer Graphics Research IGD Germany TU Darmstadt Germany Norwegian University of Science and Technology Norway TYAI China VICOMTECH Spain University of the Basque Country Spain SiMiT Lab Istanbul Technical University Turkey ACES Inc Japan Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China University of Ljubljana Slovenia University of Melbourne Australia University of Moratuwa Sri Lanka National University of Singapore Singapore INESC TEC Portugal University of Porto Portugal

This paper presents a summary of the Masked Face Recognition Competitions (MFR) held within the 2021 International Joint Conference on Biometrics (IJCB 2021). The competition attracted a total of 10 participating teams with valid submissions. The affiliations of these teams are diverse and associated with academia and industry in nine different countries. These teams successfully submitted 18 valid solutions. The competition is designed to motivate solutions aiming at enhancing the face recognition accuracy of masked faces. Moreover, the competition considered the deployability of the proposed solutions by taking the compactness of the face recognition models into account. A private dataset representing a collaborative, multisession, real masked, capture scenario is used to evaluate the submitted solutions. In comparison to one of the top-performing academic face recognition solutions, 10 out of the 18 submitted solutions did score higher masked face verification accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Biometrics

Frontal Left Alpha Activity as an Indicator of Willingness to Interact with Virtual Agents: A pilot study

学校读者我要写书评

暂无评论

Frontal Left Alpha Activity as an Indicator of Willingness t...

International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Betul Tolgay Mauro Maldonato Carl Vogel Gennaro Cordasco Luigi Trojano Anna Esposito Universit'a degli Studi della Campania “L. Vanvitelli” Università di Napoli “Federico II” Naples Italy School of Computer Science and Statistics Trinity College Dublin Ireland International Institute for Advanced Scientific Studies (IIASS) Italy

ISBN: (数字)9781728182131

ISBN: (纸本)9781728182148

Over the last decade, much effort has been made to develop virtual agents acting as assistants of elderly people in their daily activities. With the emergence of such technologies, several questionnaires have been developed to investigate the factors increasing user's acceptance of virtual agents. While questionnaires provide detailed information about users' preferences, they may not be sufficient for investigating user's internal affective states and impressions during the interaction with virtual agents. Therefore, improving assessment techniques for elders' acceptance of virtual agents is necessary for understanding the impressions they arouse and determining their design accordingly. This paper is a report of a pilot study that benefits from the predictive ability of left frontal alpha activity in the brain on positive affect and approach related motivation, and investigates relationships between user's willingness to interact with virtual agents and left frontal alpha activity in order to gain insights on user's affective and motivational states during the interaction with an agent.

关键词： Assistive technology Conferences Senior citizens Aging Electroencephalography Real-time systems

Behavioral Sentiment Analysis of Depressive States

学校读者我要写书评

暂无评论

Behavioral Sentiment Analysis of Depressive States

International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Anna Esposito Gennaro Raimo Mauro Maldonato Carl Vogel Massimiliano Conson Gennaro Cordasco Universita degli Studi della Campania “L. Vanvitelli” International Institute for Advanced Scientific Studies (IIASS) Italy Universita di Napoli “Federico II” Naples Italy School of Computer Science and Statistics Trinity College Dublin Ireland

ISBN: (数字)9781728182131

ISBN: (纸本)9781728182148

The need to release accurate and incontrovertible diagnoses of depression has fueled the search for new methodologies to obtain more reliable measurements than the commonly adopted questionnaires. In such a context, research has sought to identify non-biased measures derived from analyses of behavioral data such as voice and language. For this purpose, sentiment analysis techniques were developed, initially based on linguistic characteristics extracted from texts and gradually becoming more and more sophisticated by adding tools for the analyses of voice and visual data (such as facial expressions and movements). This work summarizes the behavioral features accounted for detecting depressive states and sentiment analysis tools developed to extract them from text, audio, and video recordings.

关键词： Sentiment analysis Databases Tools Linguistics Depression Feature extraction Stress

Spectrum of QCD with one flavor: A window for supersymmetric dynamics

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Morte, Michele Della Jäger, Benjamin Sannino, Francesco Tsang, Justus Tobias Ziegler, Felix P.G. CP3-Origins Dept. of Mathematics and Computer Science University of Southern Denmark Odense M5230 Denmark Danish Institute for Advanced Study University of Southern Denmark Odense M5230 Denmark CP3-Origins Dept. of Physics Chemistry and Pharmacy University of Southern Denmark Odense M5230 Denmark Dipartimento di Fisica "E. Pancini" Università di Napoli Federico II INFN sezione di Napoli Complesso Universitario di Monte S. Angelo Napoli80126 Italy CERN Theoretical Physics Department Geneva 231211 Switzerland School of Physics and Astronomy The University of Edinburgh EdinburghEH9 3FD United Kingdom

We compute the spectrum of the low-lying mesonic states with vector, scalar and pseudoscalar quantum numbers in QCD with one flavour. With three colours the fundamental and the two-index anti-symmetric representations of the gauge group coincide. The latter is an orientifold theory that maps into the bosonic sector of N = 1 super Yang-Mills theory in the large number of colours limit. We employ Wilson fermions along with tree-level improvement in the gluonic and fermionic parts of the action. In this setup the Dirac operator can develop real negative eigenvalues. We therefore perform a detailed study in order to identify configurations where the fermion determinant is negative and eventually reweight them. We finally compare results with effective field theory predictions valid in the large NC limit and find reasonably consistent values despite NC being only three. Additionally, the spin-one sector provides a novel window for supersymmetric dynamics. © 2023, CC BY-NC-SA.

关键词： Eigenvalues and eigenfunctions