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Contextual Augmentation with Bias Adaptive for Few-Shot Video Object Segmentation 30th

Contextual Augmentation with Bias Adaptive for Few-Shot Vi...

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30th International Conference on MultiMedia Modeling, MMM 2024

作者： Wang, Shuaiwei Liu, Zhao Lei, Jie Feng, Zunlei Xu, Juan Li, Xuan Liang, Ronghua College of Computer Science Zhejiang University of Technology Hangzhou China College of Computer Science Zhejiang University Hangzhou China Ping An Life Insurance of China Ltd. Shanghai China

ISBN: (纸本)9783031533044

Few-shot video object segmentation (FSVOS) is a challenging task that aims to segment new object classes across query videos with limited annotated support images. Typically, meta learner is the main approach to handle few-shot tasks. However, the current meta learner ignores contextual information and lacks the use of temporal information in videos. Moreover, the trained models are biased towards the segmentation of novel classes, favoring the seen class, which hinders the recognition of novel classes. To address these problems, we propose contextual augmentation with bias adaptive for few-shot video object segmentation, consisting of a context augmented learner (CAL) and a bias adaptive learner (BAL). The context augmented learner processes the contextual information in the video and guides the meta learner to obtain rough prediction results. Afterwards, the bias adaptive learner adapts to the bias of the novel classes. The BAL branch utilizes a base class learner to identify the base classes and compute the similarity between the query video and the support set, guiding the adaptive integration of coarse-robust results to generate accurate segmentation. Experiments conducted on the Youtube-VIS dataset demonstrate that our approach achieves state-of-the-art performance. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image segmentation

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computer Systems Analysis Focused on the Detection of Violence Against Women: Challenges in Data science 12th

Computer Systems Analysis Focused on the Detection of Violen...

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12th World Conference on Information Systems and Technologies (WorldCIST)

作者： Cruz-Mendoza, Mariana-Carolyn Melendez-Armenta, Roberto Angel Lopez-Mendez, Maria Cristina Velazquez-Carmona, Narendra Inst Tecnol Super Misantla Tecnol Nacl Mexico Div Estudios Posgrad & Invest Misantla 93821 Veracruz Mexico Tecnol Nacl Mexico Valle de Bravo Div Ingn Sistemas Computac Km 31 Carretera Monumento Valle De Bravo Mexico

ISBN: (纸本)9783031602269;9783031602276

Violence against women has increased. Throughout time, various strategies have been implemented to eradicate this public health problem. Researchers with diverse professional profiles have joined forces to propose solutions in the area of computer sciences. In this article, a systematic revision on the technologies implemented to eradicate violence against women was carried out, applying the PRISMA methodology. The country with the most research in the area of Artificial Intelligence is the United States of America. Research is focused on the predictive analysis of violence in different contexts, and studies related to Neural Networks and the treatment of medical reports data are the ones that are most similar to the analysis of partner violence. However, no evidence was found that predictions were made to prevent feminicide. This is why implementing data science in reports of violent incidents against women is imperative to restructure the protocol of action in governmental institutions and, with it, prevent the risk of feminicide.

关键词： Data science Artificial Intelligence Intimate Partner Violence Feminicide

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Handwriting Intra-Variability Across Surface Transitions: Implications for Writer Identification 27th

Handwriting Intra-Variability Across Surface Transitions: Im...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Priya, Kumari Adak, Chandranath Chaudhuri, Bidyut B. Blumenstein, Michael Department of CSE Indian Institute of Technology Patna Patna801106 India Department of CSE Techno India University Salt Lake City Kolkata700091 India FEIT University of Technology Sydney Ultimo2007 Australia

ISBN: (纸本)9783031784972

Handwriting exhibits intra-variability within the same writer due to friction between different writing surfaces, such as transitioning from paper to a computer tablet. This study investigates such intra-variability in handwriting characteristics across different writing surfaces and its implications for writer identification. An empirical study is conducted to assess the performance of state-of-the-art deep architectures in identifying writers amidst such intra-variation. Additionally, a transformer-based model is proposed to capture writer identification under these intra-variable circumstances. A dataset comprising 1560 handwritten English text-line images from 130 writers is created and utilized for experimentation. The results reveal insightful outcomes regarding the utilization of deep architectures and the proposed model in handling intra-variability for writer identification. This study contributes to advancing the understanding of intra-variability in handwriting and offers practical implications for forensic analysis and document authentication in the digital age. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： computer forensics

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Empowering Mobility: Brain-computer Interface for Enhancing Wheelchair Control for Individuals with Physical Disabilities 18th

Empowering Mobility: Brain-Computer Interface for Enhancing ...

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18th International Conference on Universal Access in Human-computer Interaction (UAHCI) Held as Part of the 26th International Conference on Human-computer Interaction (HCII)

作者： Ghasemi, Shiva Gracanin, Denis Azab, Mohammad Virginia Tech Blacksburg VA 24060 USA Virginia Mil Inst Lexington VA 24459 USA

ISBN: (纸本)9783031608834;9783031608841

The integration of brain-computer interfaces (BCIs) into the realm of smart wheelchair (SW) technology signifies a notable leap forward in enhancing the mobility and autonomy of individuals with physical disabilities. BCIs are a technology that enables direct communication between the brain and external devices. While BCIs systems offer remarkable opportunities for enhancing human-computer interaction and providing mobility solutions for individuals with disabilities, they also raise significant concerns regarding security, safety, and privacy that have not been thoroughly addressed by researchers on a large scale. Our research aims to enhance wheelchair control for individuals with physical disabilities by leveraging electroencephalography (EEG) signals for BCIs. We introduce a non-invasive BCI system that utilizes a neurosignal acquisition headset to capture EEG signals. These signals are obtained from specific brain activities that individuals have been trained to produce, allowing for precise control of the wheelchair. EEG-based BCIs are instrumental in capturing the brain's electrical activity and translating these signals into actionable commands. The primary objective of our study is to demonstrate the system's capability to interpret EEG signals and decode specific thought patterns or mental commands issued by the user. By doing so, it aims to convert these into accurate control commands for the wheelchair. This process includes the recognition of navigational intentions, such as moving forward, backward, or executing turns, specifically tailored for wheelchair operation. Through this innovative approach, we aim to create a seamless interface between the user's cognitive intentions and the wheelchair's movements, enhancing autonomy and mobility for individuals with physical disabilities.

关键词： Accessibility BCI EEG Smart wheelchair

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Towards a Smarter Tomorrow: A Design science Perspective on Building a Smart Campus IoT Data Platform 19th

Towards a Smarter Tomorrow: A Design Science Perspective on ...

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19th International Conference on Design science Research in Information Systems and Technology (DESRIST) - Design science Research for a Resilient Future

作者： Blazevic, Mevludin Aldenhoff, Timon T. Riehle, Dennis M. Univ Koblenz Univ Str 1 D-56070 Koblenz Germany

ISBN: (纸本)9783031611742;9783031611759

In the area of Internet of Things (IoT) data storage, the integration of Relational Database Management Systems (RDBMS) and Time Series Database (TSD) approaches represents a promising reliable, and scalable solution. This paper aims to design and instantiate a reference architecture for an IoT data platform tailored for a smart campus or University of Things (UoT) environment. The approach includes combining RDBMS and TSD technologies within a single, unified data platform. This integration combines relational data, which is commonly used in Information Systems (IS), with time-stamped information from various IoT sensors deployed across the university campus. The collected sensor data comprises millions of data points over time, which are effectively integrated into the IoT data platform, facilitating quick and dependable access to time series data, and eliminating the need for complex preprocessing or indexing. By applying the Action Design Research (ADR) method, requirements for the data platform derived from the existing smart campus infrastructure are gathered before designing the platform. The findings reveal that combining RDBMS and TSDs concepts represents an easy-to-implement and scalable solution for IoT infrastructures.

关键词： Internet of Things Data Platform IoT Data Storage Time Series Database Relational Database

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Compositional Techniques for Boolean Networks and Attractor Analysis 43rd

Compositional Techniques for Boolean Networks and Attracto...

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43rd International Conference on Application and Theory of Petri Nets and Concurrency , Petri Nets 2022

作者： Abdulrahman, Hanin Steggles, Jason Faculty of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh Saudi Arabia School of Computing Newcastle University Newcastle upon Tyne United Kingdom

ISBN: (纸本)9783662681909

Recently a new compositional framework for constructing and analysing Boolean networks was presented based on merging entities using Boolean connectives. While this framework provides a good basis for engineering Boolean networks, its practical application is limited by the restricted composition structures allowed and the lack of support for attractor analysis. In this paper we significantly extend this compositional framework by developing a new general structure for compositions and by providing new techniques for compositionally identifying the attractors of a Boolean network. The results presented are important as they support ongoing work to use the framework for engineering biological systems and also provide a new basis for analysing Boolean networks which helps to address the practical limitations imposed by the state space explosion problem. © 2024, The Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature.

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What Affects the Success of Programmers in Query Validation Process? An Eye Tracking Study

What Affects the Success of Programmers in Query Validation ...

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Human Interface and the Management of Information (HIMI) part of International Conference on Human-computer Interaction (HCII)

作者： Mishra, Deepti Inal, Yavuz Norwegian Univ Sci & Technol Dept Comp Sci Gjovik Norway Inland Norway Univ Appl Sci Lillehammer Norway Norwegian Univ Sci & Technol Dept Design Gjovik Norway

ISBN: (纸本)9783031351280;9783031351297

A meticulous examination of SQL queries plays a pivotal role in the process of learning SQL. It is important to understand the procedures utilized by students in SQL query formulation, but there has been insufficient attention given to this direction in recent literature. Therefore, we aim to explore the nature of different approaches of students in understanding SQL questions, along with the given relations to formulate correct SQL queries. We conducted an eye-tracking study with 27 university students to investigate differences in strategies through the difficulty levels of tasks. Overall, we found that differences in the strategies of students have an effect on formulating correct SQL queries. Students who successfully completed the tasks spent more time and had a higher fixation count in all areas of interest, including the question, table, and solution. Moreover, these students took longer in each area of interest to complete the query validation process as the tasks increased in difficulty. The heatmap data revealed that the students who failed the tasks did not follow the same reading order as those who succeeded. The successful students read the SQL from the first line to the last, whereas the unsuccessful students did not adhere to this sequential approach.

关键词： Query Validation SQL Programming computer science Education Eye Tracking

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Learning 2D Human Poses for Better 3D Lifting via Multi-model 3D-Guidance 17th

Learning 2D Human Poses for Better 3D Lifting via Multi-mo...

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17th Asian Conference on computer Vision, ACCV 2024

作者： Lee, Sanghyeon Hwang, Yoonho Lee, Jong Taek School of Computer Science and Engineering Kyungpook National University Daegu Korea Republic of

ISBN: (纸本)9789819608843

Recent advancements in 2D pose detectors have significantly improved 3D human pose estimation via the 2D-to-3D lifting approach. Despite these advancements, a substantial accuracy gap remains between using ground-truth 2D poses and detected 2D poses for 3D lifting. However, most methods focus solely on enhancing the 3D lifting network, using 2D pose detectors optimized for 2D accuracy without any refinement to better serve the 3D lifting process. To address this limitation, we propose a novel 3D-guided training method that leverages 3D loss to improve 2D pose estimation. Additionally, we introduce a multi-model training method to ensure robust generalization across various 3D lifting networks. Extensive experiments with three 2D pose detectors and four 3D lifting networks demonstrate our method’s effectiveness. Our method achieves an average improvement of 4.6% in MPJPE on Human3.6M and 16.8% on Panoptic, enhancing 2D poses for accurate 3D lifting. The code is available at https://***/knu-vis/L2D-Pose. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Digital elevation model

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The Missing Linkage Between science Technology and Innovation Policy and the Scientific Workforce—Evidence from Colombia 19th

The Missing Linkage Between Science Technology and Innovatio...

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19th International Conference on Wisdom, Well-Being, Win-Win, iConference 2024

作者： Cortés, Julián D. Ramírez-Cajiao, María Catalina School of Management and Business Universidad del Rosario Bogotá Colombia Engineering School Universidad de Los Andes Bogotá Colombia

ISBN: (纸本)9783031578496

STIP (science, technology, and innovation policy/es) strive to give direction and incentives to the formation and specialization of the scientific workforce. How to draw the linkage between both factors of the national STI system? Here we explore the correlation between highly strategic research areas/fields supported by STIP and the scientific workforce of Colombia from 2013 to 2021. We used a dataset of 225 research funding calls and a sample of 28,000 + scientist profiles. We found no statistically significant correlation between both variables. Our discussion orbited around government STIP transitions, STIP models, and STIP timing of implementation. Our contribution lies in proposing a standardized and replicable diagnosis to identify strategic research areas/fields supported by STIP to the absent literature on STIP-scientific workforce relationship in the contexts of middle and low-income countries. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Engineering research

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MatTrans: Material Reflectance Property Estimation of Complex Objects with Transformer 12th

MatTrans: Material Reflectance Property Estimation of Compl...

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12th International Conference on Computational Visual Media, CVM 2024

作者： Wu, Liping Cheng, Bin Chao, Wentao Zhao, Juli Duan, Fuqing School of Artificial Intelligence Beijing Normal University Beijing100875 China School of Data Science and Software Engineering Qingdao University Qingdao266071 China

ISBN: (纸本)9789819720941

Material Reflectance Property Estimation of an object is challenging and it can be used in realistic rendering to make the appearance of objects realistic. Current research focuses primarily on the near-planar objects, with little attention paid to complex-shaped objects. In this paper, we propose a method called MatTrans to estimate geometry and material reflectance properties with Transformer. Specifically, a Transformer Encoder module is designed to fuse local and global information for each material property respectively, and then a cascaded network with residual learning is introduced to estimate the geometry and reflectance properties of any 3D object surface from a single image. Extensive experiments validate that our method brings a clear improvement over previous methods for single-shot capture of spatially varying BRDFs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Reflection

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