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17th Asian Conference on Computer Vision, ACCV 2024

作者： Mok, Dahyun Bum, Junghyun Tai, Le Duc Choo, Hyunseung Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9789819609000

Diabetic Retinopathy (DR) is a primary cause of blindness, necessitating early detection and diagnosis. This paper focuses on referable DR classification to enhance the applicability of the proposed method in clinical practice. We develop an advanced cross-learning DR classification method leveraging transfer learning and cross-attention mechanisms. The proposed method employs the Swin U-Net architecture to segment lesion maps from DR fundus images. The Swin U-Net segmentation model, enriched with DR lesion insights, is transferred to generate a lesion map. Both the fundus image and its segmented lesion map are used as complementary inputs for the classification model. A cross-attention mechanism is deployed to improve the model’s ability to capture fine-grained details from the input pairs. Our experiments, utilizing two public datasets, FGADR and EyePACS, demonstrate a superior accuracy of 94.6%, surpassing current state-of-the-art methods by 4.4%. To this end, we aim for the proposed method to be seamlessly integrated into clinical workflows, enhancing accuracy and efficiency in identifying referable DR. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image segmentation

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Improving Occluded Human Pose Estimation Via Linked Joints 48

Improving Occluded Human Pose Estimation Via Linked Joints

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Ye, Suhang Hong, Zebo Zheng, Jiawen Zhang, Shengchuan Xiamen University Media Analytics and Computing Laboratory Department of Artificial Intelligence School of Informatics China

ISBN: (纸本)9781728163277

Keypoint heatmaps, which produce peak values of Gaussian distributions for individual human joints, are crucial components in 2D human pose estimation. However, existing merits using keypoint heatmaps are usually defeated in body occlusion, resulting in inaccurate joint predictions. We consider that the failure is mainly due to keypoint heatmaps' insufficiency for distinguishing the joints from two occluded bodies. Therefore, in this paper, we propose a method termed SkeletonMap (SMap), which introduces the prior knowledge of body structure to constrain relative connection of joints. As an extension of keypoint heatmaps, SMap can be efficiently plugged into existing 2D human pose estimation models with negligible increase in computational cost. Extensive experiments are conducted to show the effectiveness and generalization of SMap. Without bells and whistles, SMap brings a significant performance boost to the existing heatmap-based 2D human pose estimation models. On the MPII dataset, SMap improves SimpleBaseline (ResNet-152) from89.7 PCKh@0.5 to 90.4, and HRNet (W32) from 90.5 to 90.9. On the COCO dataset, SMap improves SimpleBaseline (ResNet-152) from 72.4 AP to 73.9. On the more challenging OCHuman dataset, SMap improves HRNet (W32) from 61.9 AP to 64.5, achieving 2.6 AP gains. We hope our simple and efficient approach will serve as a solid component for future research in 2D human pose estimation. © 2023 IEEE.

关键词： Computer vision

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NDAS: Noise-Decomposed Abnormal Segmentation for Robust Medical Image Retrieval 19

NDAS: Noise-Decomposed Abnormal Segmentation for Robust Medi...

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19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Kim, Ju-Chan Van Nguyen, Pham Le, Duc-Tai Choo, Hyunseung College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9798331507817

This paper presents NDAS (Noise-Decomposed Abnormal Segmentation), an innovative framework for robust medical image retrieval and segmentation. By explicitly decomposing noise and abnormal features, NDAS enhances retrieval accuracy and segmentation precision. Experimental results on the BraTS 2019 dataset validate NDAS’s superiority over CBMIR and SBMIR methods, achieving the highest Top-5 accuracy and Dice coefficient. This demonstrates its effectiveness in handling noise, isolating pathological regions, and retrieving diagnostically relevant medical images. NDAS offers a significant advancement in medical imaging analysis, emphasizing its potential for clinical applications requiring precision and reliability. © 2025 IEEE.

关键词： Image segmentation

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i-NVMe: Isolated NVMe over TCP for a Containerized Environment 42

i-NVMe: Isolated NVMe over TCP for a Containerized Environme...

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42nd IEEE International Conference on Computer Communications, INFOCOM 2023

作者： Lee, Seongho Yeom, Ikjun Kim, Younghoon College of Computing and Informatics Sungkyunkwan University Department of Computer Science and Engineering Suwon Korea Republic of

ISBN: (纸本)9798350334142

Non-Volatile Memory Express (NVMe) over TCP is an efficient technology for accessing remote Solid State Drives (SSDs);however, it may cause a serious interference issue when used in a containerized environment. In this study, we propose a CPU isolation scheme for NVMe over TCP in such an environment. The proposed scheme measures the CPU usage of the NVMe over TCP worker, charges it to containers in proportion to their NVMe traffic, and schedules containers to ensure isolated sharing of the CPU. However, because the worker runs with a higher priority than normal containers, it may not be possible to achieve CPU isolation with container scheduling alone. To solve this problem, we also control the CPU usage of the worker by throttling NVMe over TCP traffic. The proposed scheme is implemented on a real testbed for evaluation. We perform extensive experiments with various workloads and demonstrate that the scheme can provide CPU isolation even in the presence of excessive NVMe traffic. © 2023 IEEE.

关键词： Containers

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An approach for measuring spatial similarity among COVID-19 epicenters

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Geo-Spatial Information Science 2023年第3期26卷 496-513页

作者： Neda Kaffash Charandabi Abolghasem Sadeghi-Niaraki Soo-Mi Choi Tamer Abuhmed Geomatic Department Marand Technical FacultyUniversity of TabrizTabrizIran Department of Computer Science and Engineering and Convergence Engineering for Intelligent Drone Sejong UniversitySeoulSouth Korea College of Computing and Informatics Sungkyunkwan UniversitySuwonSouth Korea

Most countries and territories worldwide are affected by coronavirus disease 2019(COVID-19),and some cities have become known as epicenters owing to high *** of the changeable and unknown nature of the virus,managers of different cities could learn from the experiences of cities that have been successful in controlling COVID-19 instead of wasting time exploring different *** would be even more beneficial if they analyzed the experiences of similar *** similarity of such cities could be examined within a geographic information system based on various *** study investigated the similarities among eight cities-Wuhan,Tehran,Bergamo,Madrid,Paris,Daegu,New York,and Berlin-in terms of the COVID-19 situation(target)in these locations based on proximity factors,weather,and demographic ***,the factor and target layers were prepared,and then similar cities were identified using a similarity model and different distance *** results were aggregated using the Copeland method because of the different outcomes for each *** most similar city was identified for each selected city,and its similarity level was determined based on these *** results suggested the following pairs of similar cities:Wuhan-Berlin,Tehran-Berlin,Daegu-Wuhan,Bergamo-Madrid,Paris-Madrid,and New York-Paris based on COVID-19 related data up to 15 April 2020(target T1),and Daegu-Wuhan,Tehran-Madrid,Bergamo-Paris,Berlin-Paris,and New York-Madrid up to 8 December 2021(target T2)with a minimum and maximum similarity rate of 82.85%and 92.36%,*** similar cities,the most similar factors among the proximity criteria are the distance from bus and metro stations;among weather,the criteria are humidity and pressure;and among demographics,the criteria are male and female population ratios,literacy ratio,and death ratio from asthma and cancer,with a minimum and maximum difference of 0%and 64.94%,*** addition,according to the rando

关键词： COVID-19 GIS spatial similarity environmental factors demographic factors

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An ETSI-Compliant Architecture for the Element Management System: The Key for Holistic NFV Management 19

An ETSI-Compliant Architecture for the Element Management Sy...

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19th International Conference on Network and Service Management, CNSM 2023

作者： Fulber-Garcia, Vinicius Flauzino, Jose Dos Santos, Carlos R. P. Duarte, Elias P. Federal University of Paraná Department of Informatics Brazil Federal University of Santa Maria Department of Applied Computing Brazil

ISBN: (纸本)9783903176591

The Element Management System (EMS) is defined by the ETSI NFV reference architecture as responsible for the instrumentation of Virtualized Network Functions (VNF). The EMS acts as a gateway to each function, executing monitoring and control requests received from the VNF Manager (VNFM) and Operation and Business Support Systems (OSS/BSS). Surprisingly, the EMS has been either entirely ignored or only employed in very restricted settings. In this work, we propose an ETSI-compliant architecture that allows the development of EMS solutions that can be used to manage arbitrary VNF instances while abstracting particular protocols and technologies, thus enabling the interoperability among heterogeneous systems (VNF, VNFM, and OSS/BSS). The architecture was implemented as the Holistic, Lightweight, and Malleable EMS Solution (HoLMES). Evaluation results are presented showing the overhead of using HoLMES as a gateway for typical management operations. The slight increase in execution times is a fair price to pay for the benefits that the holistic solution represents in terms of the effectiveness of NFV management. © 2023 IFIP.

关键词： Gateways (computer networks)

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Performance Evaluation of Contextualized Arabic Embeddings: The Arabic Sentiment Analysis Task

Performance Evaluation of Contextualized Arabic Embeddings: ...

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International Conference on Data Analytics and Management, ICDAM 2022

作者： Dakalbab, Fatima Elnagar, Ashraf Department of Computer Science College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9789811976148

Sentiment analysis is a growing topic of study that straddles several disciplines, consisting of machine learning, natural language processing, and data mining. Its goal is to automate the extraction of conveyed concepts from a text. Much research has been undertaken in this field, particularly on English texts, because of their wide uses, whereas other languages, like Arabic, have gotten far less attention. The objective is to implement a multi-classification sentiment analyzer for Arabic text while using four recently published contextualized embedding models. The proposed work is an intrinsic evaluation metric of the four models. The results of the experiments revealed that MARBERT and ARABERT models are found to be the best. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sentiment analysis

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Adoption of Digital Health Technologies in Supported Living Services 10

Adoption of Digital Health Technologies in Supported Living ...

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10th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2024

作者： Elimian, Peter Kiyak, Ceyda Cetinkaya, Deniz Department of Computing and Informatics Bournemouth University Poole United Kingdom School of Psychology University of East Anglia Norwich United Kingdom

ISBN: (纸本)9789897587009

The adoption of digital health technologies in supported living services has shown great potential to revolutionise the quality of support offered to service users who are predominantly adults with learning disabilities and mental health conditions. Despite these potential benefits, the adoption of these technologies in supported living services remains at a low level. Therefore, this study aimed to address this gap by investigating the factors influencing the adoption of digital health technologies in supported living services. The research employed a mixed-method approach, conducting a case study in two local supported living services with a sample size of six participants, three from each service. Analysis of the collected data, utilizing both descriptive statistics and thematic approaches, revealed that 83.3% of participants acknowledged widespread acceptance of digital health technologies in the services. Notably, 66.7% highlighted the prevalence of health monitoring and assistive technology devices, including blood pressure monitors, blood glucose monitors, mobility scooters, and virtual assistants. Participants attributed the positive adoption environment to facilitation factors such as enhanced funding, training initiatives, and organizational support. Furthermore, most participants emphasized the essential need for a medication reminder app, expressing a preference for an easy-to-use and user-friendly design. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Blood

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The application of distributed autonomous organization governance mechanisms to civic medical data management

IET Blockchain

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IET Blockchain 2024年第S1期4卷 507-525页

作者： Cunningham, James Davies, Nigel Devaney, Sarah Holm, Søren Harding, Mike Neumann, Victoria Ainsworth, John Division of Informatics Imaging and Data Sciences University of Manchester Manchester United Kingdom Department of Computing and Communications Lancaster University Lancaster United Kingdom CSEP Department of Law School of Social Sciences The University of Manchester Manchester United Kingdom

Decentralized autonomous organizations (DAOs) have emerged as a novel governance mechanism that operates through distributed ledgers and smart contracts, enabling members to direct an organization's actions. The widespread adoption of DAOs has occurred in response to their utility in managing emergent semi-structured projects and has led to the development of various innovative governance mechanisms. The mechanisms employed by DAOs has the potential to be generalized beyond their core financial domain to a wide range of use cases. In the medical field the use of blockchain and DAOs can provide secure and transparent access to medical data, while ensuring patient privacy. Civic access to medical data is a growing area of interest, where individuals have control over their own medical data and can share it with healthcare providers, researchers, and other stakeholders. DAOs can facilitate this civic access, enabling individuals to share their data securely and selectively with authorized parties for research and other purposes. This paper explores the use of DAOs to medical data sharing, with a focus on ownership, governance, and transaction models. An application framework and API that enables the deployment of DAO-like organizations is derived and this approach is applied to the patient-centric management of medical data. © 2024 The Author(s). IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： Blockchain

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Using classification and visualization to support clinical texts review in electronic clinical documentation 22

Using classification and visualization to support clinical t...

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6th International Conference on Medical and Health informatics, ICMHI 2022

作者： Kenei, Jonah Kipchirchir Opiyo, Elisha Department of Computing & Informatics University of Nairobi Kenya Kenya

ISBN: (纸本)9781450396301

Electronic health records, as a repository, of patient information, is nowadays the most commonly used technology to record , store and review patient clinical records and perform other clinical tasks. However, the accurate identification and retrieval of relevant information from clinical records is a difficult task due to the unstructured nature of clinical documents, characterized in particular by lack of clear structure. Therefore, medical practice is facing a challenge thanks to rapid growth of health information in electronic health records (EHRs), mostly in narrative text form. As a result, it's becoming important to effectively manage the growing amount of data for a single patient and there is currently a requirement to visualize electronic health records (EHRs) in a way that aids physicians in clinical tasks and medical decision-making. Leveraging text visualization techniques to unstructured clinical narrative texts is a new area of research that aims to provide better information extraction and retrieval to support clinical decision support in scenarios where data generated continues to grow. Clinical datasets in electronic health records (EHR) offer a lot of potential for training accurate statistical models to classify facets of information which can then be used to improve patient care and outcomes. However, in many clinical note datasets, unstructured nature of clinical texts is a common problem. This paper examines to the very issue of getting raw clinical texts and mapping them into meaningful structures that can support healthcare professional utilizes narrative texts. Our work is the result of a collaborative design process that was aided by empirical data collected through formal usability testing. © 2022 Owner/Author.

关键词： Classification (of information)

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