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Image Fusion Based on Feature Decoupling and Proportion Preserving 1

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18th International Conference on computer-Aided Design and computer Graphics (CAD/Graphics)

作者： Fang, Bin Yi, Ran Ma, Lizhuang Shanghai Jiao Tong Univ Shanghai 200240 Peoples R China Shanghai Key Lab Comp Software Evaluating & Testi Shanghai 201112 Peoples R China

ISBN: (数字)9789819996667

ISBN: (纸本)9789819996650;9789819996667

Image fusion is a widely used technique for generating a new image by combining information from multiple input images. However, existing image fusion algorithms are often domain-specific, which limits their generalization ability and processing capacity. In this paper, we propose a fast unified fusion network called FDF, based on feature decoupling and intensity and gradient feature proportion maintenance. FDF is an end-to-end network that can perform multiple image fusion tasks. We first decouple the features of the source images into intensity features and texture features and then fuse them using the intensity and gradient paths. To improve the generalization ability, we design a unified loss function that can adapt to different fusion tasks. We evaluate FDF on three image fusion tasks, namely visible and infrared image fusion, multi-exposure image fusion, and medical image fusion. Our experimental results show that FDF outperforms state-of-the-art methods in terms of visual effects and multiple quantitative metrics. The proposed method has the potential to be applied to other image fusion tasks and domains, making it a promising approach for future research. Overall, FDF provides a fast and unified solution for image fusion tasks, which can significantly improve the efficiency and effectiveness of image fusion applications.

关键词： Image fusion Feature decoupling Multimodal fusion

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Automatic Meibomian Gland Segmentation and Assessment Based on TransUnet with Data Augmentation 20th

Automatic Meibomian Gland Segmentation and Assessment Based ...

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20th International Conference on Intelligent Computing (ICIC)

作者： Lai, Lingjing Wu, Yulin Fan, Jingyuan Bai, Fangrui Fan, Chao Jin, Kai Jiangnan Univ Sch Artificial Intelligence & Comp Sci Wuxi 214122 Jiangsu Peoples R China Jiangnan Univ Minist Educ Engn Res Ctr Intelligent Technol Healthcare Wuxi 214122 Jiangsu Peoples R China Sun Yat Sen Univ Affiliated Hosp 5 Dept Ophthalmol Zhuhai 519000 Guangdong Peoples R China

ISBN: (纸本)9789819755806;9789819755813

Meibomian glands (MG) are important for eyes and meibomian gland dysfunction (MGD) would lead to dry eye disease. With the development of eye imaging technology, non-contact infrared imaging named meibography has become mainstream. Physicians determine the meiboscore based on meibography images, which serves for the follow-up diagnosis. In this paper, a deep learning-based MG segmentation approach has been proposed to accurately segment meibography images. The method is based on TransUnet, which outperforms other deep learning algorithms in MG segmentation. Moreover, data augmentation is utilized to expand the limited dataset. Experiments show the dice coefficient, jaccard index, precision and recall score were achieved 0.93, 0.87, 0.94 and 0.92. Single image segmentation took 0.3 s on average. To our best knowledge, this is the first time that TransUnet and data augmentation are applied in the MG segmentation and assessment tasks.

关键词： Meibomian gland segmentation TransUnet data augmentation

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Allowing for Secure and Accessible Authentication for Individuals with Disabilities of Dexterity 10th

Allowing for Secure and Accessible Authentication for Indivi...

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10th IFIP WG 13.2 International Working Conference on Human-Centered Software Engineering (HCSE)

作者： Price, Abbie Loizides, Fernando Cardiff Univ Cardiff Wales

ISBN: (纸本)9783031645754;9783031645761

People living with disabilities of dexterity can be vulnerable to attackers when authenticating using physical input methods, such as when inputting PIN numbers using a keypad at an ATM(Cash Point), due to the extended time these interactions take because of the device's lack of accommodations and accessibility. This makes their input more observable to a potential attacker and thus compromises their security. In addition, when ease of use is severely compromised, this may cause a need to circumvent good security practices for practical usability which further makes these individuals vulnerable to potential attackers. While research in the field of accessible and secure authentication exists, limited work has focused on the unique needs of individuals who have limited to no hand or finger dexterity. This paper proposes an accessible framework for authentication (AAFIDD), that focuses on meeting the needs of this group. We implemented a prototype authentication model and present an initial user study with 7 participants that evaluated the efficacy of this prototype and the framework. Each participant was randomly assigned a PIN and asked to input it using a method reliant on hand-dexterity and then using the prototype gaze-based input. Users were timed and asked to evaluate their experience in terms of ease of use while a researcher attempted to perform an over-the-shoulder attack to evaluate the security. We found that the prototype input method was less likely to be interpreted by an observer than using a mouse to input, while users considered the prototype input method accessible and easy to use.

关键词： Pupillary Biometrics Dexterity Disability Eye-tracking Security PIN

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Tool Augmented LLMs for Big Data Analysis 1

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12th International Conference on Networked Systems (NETYS)

作者： Essabri, Mohammed Ali Rebii, Jamal Erradi, Mohammed Henceforth Rabat Rabat Morocco ENSIAS Univ Mohamed V Rabat Rabat Morocco

ISBN: (数字)9783031673214

ISBN: (纸本)9783031673207;9783031673214

Recent advancements in artificial intelligence, have been driven by the development of Large Language Models (LLMs). Following the emergence of these models, the field has witnessed remarkable progress, paving the way for unprecedented innovations. Despite these advancements, the application of LLMs in real-world systems faces challenges due to the diverse range of tools and environments, necessitating innovative approaches for practical deployment. A critical focus has been on enhancing LLMs' text-oriented question-answering capabilities through interaction with tools and APIs, aiming to reduce hallucinations and boost performance. In this paper we explore LLMs' capability for handling and learning tools for Big Data Analysis. We propose a pipeline and a methodology for developing LLMs that can interface with complex big data environments. By achieving this, we significantly lower the barriers to entry for non-expert users, enabling them to leverage big data analytics and visualization tools without requiring prior knowledge of the database type or the tools' implementation details.

关键词： Artificial Intelligence Large Language Models Tool Augmented Language Modeling Big data analysis Intelligent queries

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Privacy and Disclosure Risks in Spatial Dynamic Microsimulations 1

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International Conference on Privacy in Statistical Databases (PSD)

作者： Brenzel, Hanna Palm, Martin Weymeirsch, Jan Muennich, Ralf Fed Stat Off Destatis Gustav Stresemann Ring 11 D-65189 Wiesbaden Germany Trier Univ Univ Ring 15 D-54296 Trier Germany

ISBN: (数字)9783031696510

ISBN: (纸本)9783031696503;9783031696510

Microsimulations are used as a tool for evidence-based policy, to better understand the impact of policies on society. However, the quality of the outcome considerably depends on the quality of the data in use. In order to provide a rich set of variables on granular details, synthetic data may be involved. This becomes even more important in dynamic microsimulation where projection into the future is simulated or when providing an open data environment for the research community with a vast amount of variables including geocoded information. The present paper discusses opportunities and challenges of such synthetic but realistic data generation in a microsimulation data lab, which includes two steps of disclosure control. First, the base information which is used for the synthetic data generation has to be reviewed in terms of disclosure risks. Second, the data generating process must be ensured to not systematically reproduce rare events for (synthetic) individuals or replicating original input data. Otherwise, due to the large amount of additional information, this may lead to a cumulative effect of the individual re-identification risks. In order to make these output data of dynamic spatial microsimulations available in the sense of open and reproducible research, such statistical disclosure risks must be excluded a priori. This study examines whether disclosure risks may occur when synthetic data is generated via anonymized data from official statistics sources and how these can be avoided in principle. Furthermore, we discuss methods within the framework of spatial dynamic microsimulation frameworks that automatically ensure the standards of statistical disclosure control as well as official statistics data providers during simulation runs.

关键词： Statistical Disclosure Control Dynamic Microsimulation Synthetic Population Small Area Spatial Simualtion Monte-Carlo Simulation Confidentiality Open Reproducible Research

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A Multi-dimensional Unified Concavity and Convexity Detection Method Based on Geometric Algebra 40th

A Multi-dimensional Unified Concavity and Convexity Detectio...

引用

40th computer Graphics International Conference (CGI)

作者： Zhang, Jiyi Wei, Tianzi Liu, Ruitong Yang, Fan Wei, Yingying Wang, Jingyu Nantong Univ Sch Geog Sci Nantong 226019 Peoples R China Key Lab Spatial Informat Technol Spatial Informat Nantong 226019 Peoples R China Jiangsu Yangtze River Econ Belt Res Inst Nantong 226019 Peoples R China Chuzhou Univ Sch Geog Informat & Tourism Chuzhou 239000 Peoples R China Nantong Inst Technol Business Sch Nantong 226002 Peoples R China

ISBN: (纸本)9783031500787;9783031500770

The detection of concavity and convexity of vertices and edges of three-dimensional (3D) geometric objects is a classic problem in the field of computer graphics. As the foundation of other related graphics algorithms and operations, scholars have proposed many algorithms for determining the concavity and convexity of vertices and edges. However, existing concavity and convexity detection algorithms mainly focus on vertices and not on concavity and convexity detection methods for edges of 3D geometric objects. Furthermore, existing algorithms often require different detectionmethods when dealingwith two-dimensional (2D) planar geometric objects and 3D spatial geometric objects. This means that the algorithm structure of those algorithms becomes very complex when dealing with concavity and convexity judgments involving both planar polygon vertices and 3D geometric object edges. To solve the above problems, this paper proposes a multi-dimensional unified concave convex detection algorithm framework for geometric objects taking advantage of geometric algebra in multi-dimensional unified expression and calculation. The method proposed in this article can not only achieve concavity and convexity detection of planar polygon vertices and 3D geometric object vertices based on unified rules, but also further achieve concavity and convexity detection of 3D geometric object edges on this basis. By unifying the framework and detection rules of different dimensional geometric object concavity detection algorithms, the complexity of synchronous detection algorithms for planar polygon vertices and 3D geometric object vertices and edges concavity can be effectively simplified.

关键词： concavity-convexity detection geometric algebra outer product three-dimensional objects multi-dimensional unified

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Data Augmentation Method Utilizing Template Sentences for Variable Definition Extraction 29th

Data Augmentation Method Utilizing Template Sentences for Va...

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29th International Conference on Applications of Natural Language to Information Systems (NLDB)

作者： Nagayama, Kotaro Kato, Shota Kano, Manabu Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan

ISBN: (纸本)9783031702389;9783031702396

The extraction of variable definitions from scientific and technical papers is essential for understanding these documents. However, the characteristics of variable definitions, such as the length and the words that make up the definition, differ among fields, which leads to differences in the performance of existing extraction methods across fields. Although preparing training data specific to each field can improve the performance of the methods, it is costly to create high-quality training data. To address this challenge, this study proposes a new method that generates new definition sentences from template sentences and variable-definition pairs in the training data. The proposed method has been tested on papers about chemical processes, and the results show that the model trained with the definition sentences generated by the proposed method achieved a higher accuracy of 89.6%, surpassing existing models.

关键词： Data augmentation Variable definition extraction Document information processing

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A Process to Identify Players' Motivational Profiles for Designing a Gamification Project 24th

A Process to Identify Players' Motivational Profiles for Des...

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24th International Conference on Computational science and Its Applications (ICCSA)

作者： Ramos, Cristiane Soares Silva Farias, Mylena Angelica Andrade de Freitas, Sergio Antonio Paiva Martins, Marcus Vinicius Alves, Juan Mangueira Sampson Pinto, Leda Cardoso Univ Brasilia UnB Fac UnB Gama Area Especial Ind Proj A Gama DF Brazil Inst Brasileiro Informacao Ciencia & Tecnol IBICT Setor Autarquias Sul Quadra 5Lote 6Bloco H Brasilia DF Brazil

ISBN: (纸本)9783031646072;9783031646089

This article presents an innovative process for identifying the motivational profiles of a specific target audience using three distinct strategies: assessment by judges, application of game dynamics, and the Intrinsic Motivation Inventory (IMI) questionnaire. Each strategy aims to align with the Octalysis framework, emphasizing the importance of personalization and adaptability in gamification. The process is tested on a gamification project within a Brazilian government portal for scientific dissemination, focusing on engaging Brazilian students in science. The analysis reveals differences in strategy outcomes, highlighting the requirement of a multifaceted approach to accurately capture the target audience's motivational profiles and improve gamification effectiveness.

关键词： Gamification Motivational Profile Design Project Octalysis

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The Study of the 5-min Walking Accessibility for Pickup Points in Thessaloniki: Enhancing Logistics' Last Mile Sustainability 1

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International Conference on Computational science and Its Applications (ICCSA)

作者： Russo, Antonio Basbas, Socrates Bouhouras, Efstathios Tesoriere, Giovanni Campisi, Tiziana Univ Enna Kore Dept Engn & Architecture I-94100 Enna Italy Aristotle Univ Thessaloniki Sch Rural & Surveying Engn Thessaloniki 54124 Greece

ISBN: (数字)9783031653087

ISBN: (纸本)9783031653070;9783031653087

The UN World Health Organization deemed COVID-19 to be over as a public health emergency on May 5, 2023. Nonetheless, COVID-19 continues to impact every facet of human existence, encompassing urban planning. Today, e-commerce is a commonplace purchasing choice that has led to significant changes in city logistics, particularly in last-mile deliveries. Consequently, there is an increase in CO2 levels and traffic congestion. Therefore, there is need to analyse the existing and potential pick-up point networks, so to understand how easy it is for the user to pick up products and avoid home delivery. The present research focused in the central area of the city of Thessaloniki, Greece. The under-study area is characterised by the presence of many pick-up points which were identified with on-site surveys. Following the calculation of the 5-minwalk isochrones, itwas found that there are many (mainly) lockers. In addition, their location is mainly in the central area, while they also appear, but in reduced numbers, in the pericentre. The evaluation of accessibility reveals that 50% of the residents in the central area resides within 5 min walking distance from a pick-up point while the respective percentage is about 25% of the residents when considering the pericentre. The research findings can support the design of efficient strategies directed to the service management companies. The findings can also improve the customers' experience as far as online shopping is concerned by offering a better shopping experience, i.e., easiness to choose pick-up points, save on delivery etc.

关键词： Last mile logistics pickup point 5-min walking isochrones Thessaloniki metropolitan area

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IOCSegFormer: Enhancing Wheat Ears Counting in Field Conditions Through Augmented Local Features 20th

IOCSegFormer: Enhancing Wheat Ears Counting in Field Conditi...

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20th International Conference on Intelligent Computing (ICIC)

作者： Shen, Hualei Peng, Yilong Zhang, Jie Zang, Hecang Zhou, Meng Li, Guoqiang Liu, Dong Henan Normal Univ Coll Comp & Informat Engn Xinxiang Henan Peoples R China Key Lab Artificial Intelligence & Personalized Le Xinxiang Henan Peoples R China Big Data Engn Lab Teaching Resources & Assessment Xinxiang Henan Peoples R China Henan Acad Agr Sci Inst Agr Informat Technol Zhengzhou Peoples R China Minist Agr & Rural Areas Huanghuaihai Key Lab Intelligent Agr Technol Zhengzhou Peoples R China

ISBN: (纸本)9789819756117;9789819756124

The number of wheat ears under field conditions is pivotal for production assessment and yield forecasting. Due to the occlusion, overlap, and influence of different weather conditions, it is challenging to accurately count wheat ears with existing object counting methods, which overlook local features surrounding wheat ears. To address this issue, we propose a new deep neural network, named IOCSegFormer, to augment local features around wheat ears. Specifically, IOCSegFormer extends the existing IOCFormer object counting network by incorporating a segmentation branch responsible for generating a segmentation map delineating wheat ears. Within this branch, we introduce a local feature extraction module to enhance counting accuracy by capturing contextual information pertinent to the local surroundings. Experimental evaluations conducted on both a proprietary dataset and the Wheat Ears Detection Dataset demonstrate effectiveness of IOCSegFormer, yielding mean absolute errors of 8.39 and 12.42, and root mean square errors of 12.73 and 17.35, respectively. Comparative analysis against previous state-of-the-art methods underscores the superior performance of our model.

关键词： Object Counting Segmentation Branch Local Feature Feature Fusion

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