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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Jiang, Keyuan Devendra, Valli Chavan, Soniya Bernard, Gordon R. Purdue University Northwest Computer Information Technology & Graphics HammondIN United States Vanderbilt University Department of Medicine NashvilleTN United States

ISBN: (纸本)9798350337488

Gathering the information pertaining to health evidence occurring on particular days can help understand the progression of a disease over time, and such evidence as symptoms was widely shared by the social media users during the COVID-19 pandemic. Identifying this type of evidence is challenging. In this work, we investigated pretrained large language models on their ability to identify the day-based COVID-19 symptom mentions in Twitter posts. Our results on a corpus of 635 tweets show that without any supervision and optimization both GPT-3.5 and GPT 4 models achieved impressive performance, much better than Web-based ChatGPT and Google Bard. In addition, we explored and utilized GPT-4's ability to determine the number of matches between a list of predicted symptom expressions and a list of annotated symptom expressions, reducing the effort of designing a sophisticated algorithm for finding the matches. © 2023 IEEE.

关键词： COVID-19 symptoms day-based evidence health evidence detection large language models Twitter

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Study of the Process of Porous Materials Impregnation Using the Example of Leather Tanning 18

Study of the Process of Porous Materials Impregnation Using ...

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18th International Scientific and Technical Conference on Dynamics of Systems, Mechanisms and Machines, Dynamics 2024

作者： Damdinova, T.Ts. Radnaeva, V.D. Dept. Engineering and Computer Graphics Dept. Leather and Fur Technology. Water Resources and Commodity Research of Non-Food Goods East Siberia State University of Technology and Management Ulan-Ude Russia

ISBN: (纸本)9798331509019

The paper presents the results of the study of the process of porous materials impregnation from the point of view of percolation theory. Diffusion front, diffusion front shell, percolation cluster are determined using developed application. Processing of digital images obtained during the study of the porous object impregnation is used. This allowed obtaining the necessary quantitative characteristics of the diffusion front, percolation clusters and percolation shell. Quantitative characteristics were analyzed and kinetic curves of the impregnation process were constructed on the example of leather tanning process. As a result, the main stages of the impregnation process of the tanning composition: accumulation, percolation and distribution have been revealed. The methodology of the impregnation process study and the method of its visualization have been developed and applied to the processes of leather tanning. The universality of this development will allow applying them to the study processes in other porous materials, and in modeling and creation of new materials. © 2024 IEEE.

关键词： Leather

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DEEP LEARNING-BASED POINT CLOUD REGISTRATION FOR AUGMENTED REALITY-GUIDED SURGERY

arXiv

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arXiv 2024年

作者： Weber, Maximilian Wild, Daniel Kleesiek, Jens Egger, Jan Gsaxner, Christina Institute of Computer Graphics and Vision Graz University of Technology Austria Germany

Point cloud registration aligns 3D point clouds using spatial transformations. It is an important task in computer vision, with applications in areas such as augmented reality (AR) and medical imaging. This work explores the intersection of two research trends: the integration of AR into image-guided surgery and the use of deep learning for point cloud registration. The main objective is to evaluate the feasibility of applying deep learning-based point cloud registration methods for image-to-patient registration in augmented reality-guided surgery. We created a dataset of point clouds from medical imaging and corresponding point clouds captured with a popular AR device, the HoloLens 2. We evaluate three well-established deep learning models in registering these data pairs. While we find that some deep learning methods show promise, we show that a conventional registration pipeline still outperforms them on our challenging dataset. Copyright © 2024, The Authors. All rights reserved.

关键词： Augmented reality

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Effect of Polarization on RGB Imaging and Color Accuracy/Fidelity 30

Effect of Polarization on RGB Imaging and Color Accuracy/Fid...

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30th Color and Imaging Conference - Color Science and Engineering Systems, Technologies, and Applications, CIC 2022

作者： Haila, Tarek Abu Tausch, Reimar Ritz, Martin Santos, Pedro Fellner, Dieter W. Fraunhofer Institute for Computer Graphics Research IGD Germany Darmstadt University of Technology Germany Graz University of Technology Austria

ISBN: (纸本)9780892083626

The use of polarization while trying to keep the digital color reproduction accuracy at its finest is very challenging due to how polarization is interacting and affecting the light spectrum itself and due to the quality of the used polarization materials. Our study on RGB imaging and color reproduction's fidelity with and without polarization shows that a cross circular polarization (on a camera lens and light source) will have a major impact on how a linear grayscale, whether it has a semi-glossy or matt finishing, would be reproduced in contrast to no polarization at all. A major loss in deep black shades in the case of a semi-glossy grayscale is unmistakable. In addition to a noticeable shift in both lightness and Chroma components regardless of the grayscale's finishing but depending rather on the used color target for correction. DE00 could not paint the full picture about color fidelity despite its low conformant reported values. Whereas, a closer visual inspection of the color components separately (lightness and Chroma) reveals color reproduction problems caused by polarization. © 2022 Society for Imaging Science and technology.

关键词： Polarization

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Into the Fog: Evaluating Robustness of Multiple Object Tracking

arXiv

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arXiv 2024年

作者： Kirillova, Nadezda Mirza, M. Jehanzeb Bischof, Horst Possegger, Horst Institute of Computer Graphics and Vision Graz University of Technology Graz Austria

State-of-the-art Multiple Object Tracking (MOT) approaches have shown remarkable performance when trained and evaluated on current benchmarks. However, these benchmarks primarily consist of clear weather scenarios, overlooking adverse atmospheric conditions such as fog, haze, smoke and dust. As a result, the robustness of trackers against these challenging conditions remains underexplored. To address this gap, we introduce physics-based volumetric fog simulation method for arbitrary MOT datasets, utilizing frame-by-frame monocular depth estimation and a fog formation optical model. We enhance our simulation by rendering both homogeneous and heterogeneous fog and propose to use the dark channel prior method to estimate atmospheric light, showing promising results even in night and indoor scenes. We present the leading benchmark MOTChallenge (third release) augmented with fog (smoke for indoor scenes) of various intensities and conduct a comprehensive evaluation of MOT methods, revealing their limitations under fog and fog-like challenges. © 2024, CC BY.

关键词： Object tracking

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Sonifying motor skills with Pizzicato, a game for motor behavior research

Sonifying motor skills with Pizzicato, a game for motor beha...

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IEEE Symposium on Computational Intelligence and Games, CIG

作者： Martin Starkov Scott Jochems Joris Rijsdijk Ravi Snellenberg Luca Stoffels Amir Zaidi Rafael Bidarra Computer Graphics and Visualization Group Delft University of Technology Delft The Netherlands

ISBN: (数字)9798350350678

ISBN: (纸本)9798350350685

Learning motor skills is essential to many different aspects of life, from big movements needed for sports to small and simple movements used in the rehabilitation of stroke patients. In recent years, sonification, i.e. using sounds as feedback for actions, has been researched as a promising technique for studying motor behavior. In particular, we explore how to use sonification to make the process of learning motor skills accessible and engaging. We posit that an interactive and gamified environment can increase the engagement in that process. Moreover, an enjoyable setting is more likely to stimulate repetition, an indispensable feature of any learning endeavor. We, therefore, designed and developed Pizzicato, a rhythm-based serious game that leads players to move their arms and hands to actively play music. The game uses a common webcam to track your hand movements: pinching one finger to the thumb at the right position and moment will play musical notes that pleasantly add up to a full musical track. Our player tests have shown that players find Pizzicato accessible and engaging, and report that playing the game gives them a strong sense of agency. Pizzicato was developed in collaboration with neuropsychology colleagues, who are now starting to use it as a flexible tool for motor behavior research, both for diagnostic and rehabilitation purposes.

关键词： Visualization Tracking Webcams Thumb Music Collaboration Games

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SAda-Net: A Self-Supervised Adaptive Stereo Estimation CNN For Remote Sensing Image Data

arXiv

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arXiv 2024年

作者： Hirner, Dominik Fraundorfer, Friedrich Graz University of Technology Institute of Computer Graphics and Vision Austria Germany

Stereo estimation has made many advancements in recent years with the introduction of deep-learning. However the traditional supervised approach to deep-learning requires the creation of accurate and plentiful ground-truth data, which is expensive to create and not available in many situations. This is especially true for remote sensing applications, where there is an excess of available data without proper ground truth. To tackle this problem, we propose a self-supervised CNN with self-improving adaptive abilities. In the first iteration, the created disparity map is inaccurate and noisy. Leveraging the left-right consistency check, we get a sparse but more accurate disparity map which is used as an initial pseudo ground-truth. This pseudo ground-truth is then adapted and updated after every epoch in the training step of the network. We use the sum of inconsistent points in order to track the network convergence. The code for our method is publicly available at: https://***/thedodo/SAda-Net © 2024, CC BY.

关键词： Self-supervised learning

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Weighting Attributes Based on the Greedy Algorithm Properties 28th

Weighting Attributes Based on the Greedy Algorithm Propertie...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

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

Estimation of importance for considered features is an important issue for any knowledge exploration process and it can be executed by a variety of approaches. In the research reported in this study, the primary aim was the development of a methodology for creating attribute rankings. Based on the properties of the greedy algorithm for inducing decision rules, a new application of this algorithm has been proposed. Instead of constructing a single ordering of features, attributes were weighted multiple times. The input datasets were discretised with several algorithms representing supervised and unsupervised discretisation approaches. Each resulting discrete data variant was exploited to construct a ranking of attributes. The effectiveness of the obtained rankings was confirmed through a rule filtering process governed by weighted attributes. The methodology was applied to the stylometric task of authorship attribution. The experimental outcomes demonstrate the value of the proposed research method, as it generally led to improved predictions while taking into account a noticeably decreased sets of attributes and decision rules. © 2024 The Authors.

关键词： Consensus algorithm

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VR First Aid: Step by Step Development Process

VR First Aid: Step by Step Development Process

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Jusoh, Shaidah Al-Hiyari, Narmeen Xiamen University Malaysia School of Ee and Artificial Intelligence Selangor Sepang Malaysia Sumaya University for Technology Computer Graphics and Animation Princess Amman Jordan

ISBN: (纸本)9798350324174

Virtual reality (VR) is a simulated experience in a three-dimensional (3D) computer-simulated world. The experience could be similar to real life or completely different. Despite the fact that VR has been cited as a fantastic choice for teaching and training, the existing publications do not specifically demonstrate how to construct training application with VR technology. The purpose of this paper is to present our personal experience in designing and implementing First Aid application on Oculus Quest. © 2023 IEEE.

关键词： Virtual reality

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Oh No, Not Another Trolley! on the Need for a Co-Liberative Consciousness in CS Pedagogy

IEEE Transactions on Technology and Society

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IEEE Transactions on technology and Society 2022年第1期3卷 67-74页

作者： Williams, Rua M. Smarr, Simone Prioleau, Diandra Gilbert, Juan E. Computer Graphics and Technology Department Purdue University West LafayetteIN47907 United States Computer and Information Sciences and Engineering Department University of Florida GainesvilleFL32611 United States

Due to growing concerns for the disproportionate dangers, artificial intelligence (AI) advances pose to marginalized groups, proposals for procedural solutions to ethics in AI abound. It is time to consider that some systems may be inherently unethical, even violent, whether or not they are fair. In this article, we deploy a feminist critical discourse analysis of long-format responses to ethical scenarios from computing science undergraduate students. We find that even among students that had a strong understanding of social justice and the power of AI to exacerbate existing inequities, most students contextualize these problems as the product of biased datasets and human mis/trust factors, rather than as problems of design and purpose. Further, while many students recognized racism and classism at play in the potential negative impacts of AI systems, most students failed to recognize ableism as a driving social force for inequity. As computing science faculty, we must recognize that our students graduate to become the researchers and developers of future technosocial systems. Pedagogically, we need more than procedural fixes to systemic inequities. We are not going to program our way into justice. We must learn to say no to building violent things. © 2022 IEEE.

关键词： Students

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