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arXiv 2023年

作者： Habring, Andreas Holler, Martin Pock, Thomas Department of Mathematics and Scientific Computing University of Graz Austria Institute of Computer Graphics and Vision Graz University of Technology Austria

This paper is concerned with sampling from probability distributions π on Rd admitting a density of the form π(x) ∝ e−U(x), where U(x) = F(x) + G(Kx) with K being a linear operator and G being non-differentiable. Two different methods are proposed, both employing a subgradient step with respect to G ◦ K, but, depending on the regularity of F, either an explicit or an implicit gradient step with respect to F. For both methods, non-asymptotic convergence proofs are provided, with improved convergence results for more regular F. Further, numerical experiments are conducted for simple 2D examples, illustrating the convergence rates, and for examples of Bayesian imaging, showing the practical feasibility of the proposed methods for high dimensional *** Codes 65C40, 65C05, 68U10, 65C60 Copyright © 2023, The Authors. All rights reserved.

关键词： Inverse problems

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A Review of Satellite Image Analysis Tools 4th

A Review of Satellite Image Analysis Tools

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4th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, ICMISC 2023

作者： Pawar, Bhushan Prakash, Vijay Garg, Lalit Galdies, Charles Buttigieg, Sandra Calleja, Neville Department of Computer Information Systems Faculty of Information and Communication Technology University of Malta MSD Msida2080 Malta Department of Computer Science and Engineering Graphics Era Hill University Dehradun India Environmental Management and Plan Division Institute of Earth Systems University of Malta Msida Malta Faculty of Health Sciences University of Malta Msida Malta Faculty of Medicine and Surgery University of Malta Msida Malta

ISBN: (纸本)9789819994410

The rapid growth of urban areas, population, and pollution presents a significant environmental challenge. Addressing these challenges requires innovative analytical approaches and data sources. This study focuses on the three-scale phenomena of the environmental system, physical environment, and regional surroundings, considering their implications on a global network scale. Remote sensing data, with its easy accessibility, offers new toolkits and methods to improve the global environment. It provides self-consistent measurements of vital physical attributes and surpasses traditional data sources regarding accuracy, efficiency, and coverage of larger geographical areas. This study aims to identify and analyze appropriate satellite image analysis tools for healthcare. The study objectives include studying available tools, analyzing their features, categorizing tools into open-source and commercial categories, and providing recommendations. This study emphasizes feature extraction and image enhancement parameters, which are crucial for image analysis. Further, this study provides a functional overview of various commercial and open-source satellite image analysis tools and suggests suitable tools for healthcare applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Geographic information systems

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Satellite Image Analysis in Health Care—A Systematic Review 1

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2nd International Conference on Advances in Data-driven Computing and Intelligent Systems, ADCIS 2023

作者： Pawar, Bhushan Prakash, Vijay Garg, Lalit Galdies, Charles Buttigieg, Sandra Calleja, Neville Department of Computer Information Systems Faculty of Information and Communication Technology University of Malta MSD Msida2080 Malta Environmental Management and Plan Division Institute of Earth Systems University of Malta Msida Malta Faculty of Health Sciences University of Malta Msida Malta Faculty of Medicine and Surgery University of Malta Msida Malta Department of Computer Science Graphics Era Hill University Dehradun India

ISBN: (数字)9789819995219

ISBN: (纸本)9789819995202

Rapid urbanization, population expansion, and escalating pollution levels have given rise to novel environmental concerns that demand the application of creative, analytical methodologies and diverse data sources. To ensure efficient urban ecological management, it is crucial to consider three levels of phenomena: the environmental system, the physical environment, and the regional surroundings. Utilizing remote sensing data is a viable avenue for enhancing the global environment due to its convenient accessibility and ability to measure crucial physical features regularly. The primary objective of this research study is to ascertain and evaluate suitable methods for analyzing satellite imagery in the healthcare context. The study’s aims encompass examining the diverse array of tools accessible in the market, scrutinizing the characteristics of each device, exploring research papers that have employed these tools, and classifying the tools into open-source and commercial classifications. This study emphasizes the parameters associated with feature extraction and picture enhancement in satellite imagery, as these factors hold significant importance in the analysis of images. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Remote sensing

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M2fNet: Multi-modal Forest Monitoring Network on Large-scale Virtual Dataset

arXiv

引用

arXiv 2024年

作者： Lu, Yawen Huang, Yunhan Sun, Su Zhang, Tansi Zhang, Xuewen Fei, Songlin Chen, Victor Department of Computer Graphics Technology Purdue University United States Meta United States Department of Forestry and Natural Resources Purdue University United States

Forest monitoring and education are key to forest protection, education andmanagement, which is an effective way to measure the progress of a country\'sforest and climate commitments. Due to the lack of a large-scale wild forestmonitoring benchmark, the common practice is to train the model on a commonoutdoor benchmark (e.g., KITTI) and evaluate it on real forest datasets (e.g.,CanaTree100). However, there is a large domain gap in this setting, which makesthe evaluation and deployment difficult. In this paper, we propose a newphotorealistic virtual forest dataset and a multimodal transformer-basedalgorithm for tree detection and instance segmentation. To the best of ourknowledge, it is the first time that a multimodal detection and segmentationalgorithm is applied to large-scale forest scenes. We believe that the proposeddataset and method will inspire the simulation, computer vision, education, andforestry communities towards a more comprehensive multi-modal understanding. © 2024, CC BY-NC-SA.

关键词： Large datasets

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NeuRSS: Enhancing AUV Localization and Bathymetric Mapping with Neural Rendering for Sidescan SLAM

arXiv

引用

arXiv 2024年

作者： Xie, Yiping Zhang, Jun Bore, Nils Folkesson, John Robotics Perception and Learning Division KTH Royal Institute of Technology Stockholm Sweden The Institute of Computer Graphics and Vision Graz University of Technology Graz Austria Ocean Infinity United States

Implicit neural representations and neural rendering have gained increasing attention for bathymetry estimation from sidescan sonar (SSS). These methods incorporate multiple observations of the same place from SSS data to constrain the elevation estimate, converging to a globally-consistent bathymetric model. However, the quality and precision of the bathymetric estimate are limited by the positioning accuracy of the autonomous underwater vehicle (AUV) equipped with the sonar. The global positioning estimate of the AUV relying on dead reckoning (DR) has an unbounded error due to the absence of a geo-reference system like GPS underwater. To address this challenge, we propose in this letter a modern and scalable framework, NeuRSS, for SSS SLAM based on DR and loop closures (LCs) over large timescales, with an elevation prior provided by the bathymetric estimate using neural rendering from SSS. This framework is an iterative procedure that improves localization and bathymetric mapping. Initially, the bathymetry estimated from SSS using the DR estimate, though crude, can provide an important elevation prior in the nonlinear least-squares (NLS) optimization that estimates the relative pose between two loop-closure vertices in a pose graph. Subsequently, the global pose estimate from the SLAM component improves the positioning estimate of the vehicle, thus improving the bathymetry estimation. We validate our localization and mapping approach on two large surveys collected with a surface vessel and an AUV, respectively. We evaluate their localization results against the ground truth and compare the bathymetry estimation against data collected with multibeam echo sounders (MBES). Copyright © 2024, The Authors. All rights reserved.

关键词： Autonomous underwater vehicles

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Ranking of attributes-comparative study based on data from stylometric domain 26

Ranking of attributes-comparative study based on data from s...

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26th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2022

作者： Zielosko, Beata Stanczyk, Urszula Zabinski, Krzysztof Institute of Computer Science University of Silesia in Katowice B edzinska 39 Sosnowiec41-200 Poland Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

The area of feature selection methods constantly expands along with the development of artificial intelligence domain, and has great impact on almost every field, whenever data is processed and explored. The paper presents research where a ranking method was proposed, inspired by an approach which comes from an algorithm for induction of decision rules. The ranking procedure was based on calculation of standard deviation for attributes, taking into account assigned class labels. This method was compared with another ranking mechanism, a modified version of popular Relief algorithm, with incorporating characteristics of variables by supervised discretisation. Comparison of obtained results included the aspect of knowledge representation as well as the perspective of the accuracy for constructed rule-based classifiers. The experiments were performed on datasets from stylometry domain, where authorship attribution was considered as a classification task, and stylometric descriptors as characteristic features defining writing styles of authors. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 26th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2022)

关键词： Knowledge representation

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Perceptual navigation in absorption-scattering space 29

Perceptual navigation in absorption-scattering space

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29th Color and Imaging Conference - Color Science and Engineering Systems, Technologies, and Applications, CIC 2021

作者： Gigilashvili, Davit Urban, Philipp Thomas, Jean-Baptiste Pedersen, Marius Hardeberg, Jon Yngve Norwegian University of Science and Technology Department of Computer Science Gjøvik Norway Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany

ISBN: (纸本)9780892083572

Translucency optically results from subsurface light transport and plays a considerable role in how objects and materials appear. Absorption and scattering coefficients parametrize the distance a photon travels inside the medium before it gets absorbed or scattered, respectively. Stimuli produced by a material for a distinct viewing condition are perceptually non-uniform w.r.t. these coefficients. In this work, we use multi-grid optimization to embed a non-perceptual absorption-scattering space into a perceptually more uniform space for translucency and lightness. In this process, we rely on A (alpha) as a perceptual translucency metric. Small Euclidean distances in the new space are roughly proportional to lightness and apparent translucency differences measured with A. This makes picking A more practical and predictable, and is a first step toward a perceptual translucency space. © 2021 Society for Imaging Science and technology. All rights reserved.

关键词： Color

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Stating Comparison Score Uncertainty and Verification Decision Confidence Towards Transparent Face Recognition 33

Stating Comparison Score Uncertainty and Verification Decisi...

引用

33rd British Machine Vision Conference Proceedings, BMVC 2022

作者： Huber, Marco Terhörst, Philipp Kirchbuchner, Florian Damer, Naser Kuijper, Arjan Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Technical University of Darmstadt Darmstadt Germany Norwegian University of Science and Technology Gjøvik Norway Paderborn University Paderborn Germany

Face Recognition (FR) is increasingly used in critical verification decisions and thus, there is a need for assessing the trustworthiness of such decisions. The confidence of a decision is often based on the overall performance of the model or on the image quality. We propose to propagate model uncertainties to scores and decisions in an effort to increase the transparency of verification decisions. This work presents two contributions. First, we propose an approach to estimate the uncertainty of face comparison scores. Second, we introduce a confidence measure of the system's decision to provide insights into the verification decision. The suitability of the comparison scores uncertainties and the verification decision confidences have been experimentally proven on three face recognition models on two datasets. © 2022. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.

关键词： Face recognition

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Computed Tomography Reconstruction Using Generative Energy-Based Priors

arXiv

引用

arXiv 2022年

作者： Zach, Martin Kobler, Erich Pock, Thomas Institute of Computer Graphics and Vision Graz University of Technology Graz8010 Austria Institute of Computer Graphics Johannes Kepler University Linz Linz4040 Austria

In the past decades, Computed Tomography (CT) has established itself as one of the most important imaging techniques in medicine. Today, the applicability of CT is only limited by the deposited radiation dose, reduction of which manifests in noisy or incomplete measurements. Thus, the need for robust reconstruction algorithms arises. In this work, we learn a parametric regularizer with a global receptive field by maximizing it’s likelihood on reference CT data. Due to this unsupervised learning strategy, our trained regularizer truly represents higher-level domain statistics, which we empirically demonstrate by synthesizing CT images. Moreover, this regularizer can easily be applied to different CT reconstruction problems by embedding it in a variational framework, which increases flexibility and interpretability compared to feed-forward learning-based approaches. In addition, the accompanying probabilistic perspective enables experts to explore the full posterior distribution and may quantify uncertainty of the reconstruction approach. We apply the regularizer to limited-angle and few-view CT reconstruction problems, where it outperforms traditional reconstruction algorithms by a large margin. © 2022, CC BY.

关键词： Image reconstruction

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MultiAR: A Multi-User Augmented Reality Platform for Biomedical Education 46

MultiAR: A Multi-User Augmented Reality Platform for Biomedi...

引用

46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Perz, Markus Luijten, Gijs Kleesiek, Jens Schmalstieg, Dieter Egger, Jan Gsaxner, Christina West German Cancer Center Cancer Research Center Cologne Essen Essen Germany University of Stuttgart Institute for Visualization and Interactive Systems Stuttgart Germany Graz University of Technology Institute of Computer Graphics and Vision Graz Austria University Medicine Essen Institute for Artificial Intelligence in Medicine Essen Germany Essen Germany

ISBN: (纸本)9798350371499

This paper addresses the growing integration of Augmented Reality (AR) in biomedical sciences, emphasizing collaborative learning experiences. We present MultiAR, a versatile, domain-specific platform enabling multi-user interactions in AR for biomedical education. Unlike platform-specific solutions, MultiAR supports various AR devices, including handheld and head-mounted options. The framework extends across domains, augmenting biomedical education applications with collaborative capabilities. We define essential requirements for a multi-user AR framework in education, detail MultiAR's design and implementation, and comprehensively evaluate it using anatomy education examples. Quantitative and qualitative analyses, covering system performance, accuracy metrics, and a user study with 20 participants, highlight the urgent need for a tailored collaborative AR platform in biomedical education. Results underscore enthusiasm for collaborative AR technology, endorsing MultiAR as an accessible, versatile solution for developers and end-users in biomedical education. © 2024 IEEE.

关键词： Augmented reality

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