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检索条件"任意字段=International Conference on Frontier of Computer Science and Technology"

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Performance Analysis of BD-EMD-IMFs Fusion Based Features Extraction and Classification for Glaucoma Detection

Performance Analysis of BD-EMD-IMFs Fusion Based Features Ex...

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IEEE Students' conference on Electrical, Electronics and computer science (SCEECS)

作者： Pooja Manghnani Asmita A. Moghe Computer Science and Engineering University Institute of Technology RGPV Bhopal India Information Technology University Institute of Technology RGPV Bhopal India

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

There are various disorders in the human eye. Glaucoma is considered to be one of the most severe eye disorders. It develops with very less speed in the eye and damages all the optic nerves present inside the eyes. The outdated glaucoma prediction methods are more costly and slow. A better work about glaucoma prediction using fused bi-dimensional empirical mode decomposition- intrinsic mode functions-based feature extraction and classification from the fundus image is presented here. BD-EMD-IMFs are obtained from the preprocessed color components. Fused BD-EMD-IMFs based features extraction is the key idea of this work. Fused BD-EMD-IMFs-Based features are then normalized and classified with support vector machines (SVM). The pooled feature accuracy (Acc) reached 97.2 with 10-fold cross-validation (FCV). The experimental analysis clearly brings out the superiority of the proposed method over the traditional.

关键词： Glaucoma Support vector machines computer science Accuracy Image color analysis Prediction methods Feature extraction Optical imaging Performance analysis

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Developing a Multi-site Hyperscanning Procedure for Investigating Interbrain Synchrony Underlying Remote Social Interaction 17th

Developing a Multi-site Hyperscanning Procedure for Investig...

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17th international conference on Brain Informatics, BI 2024

作者： Limtragooltongchai, Sirapakit Yamtuan, Kawin Gracia, Javier O. Chunharas, Chaipat Sriravanasan, Ramesh Chaisilprungraung, Thitaporn Itthipuripat, Sirawaj Neuroscience Center for Research and Innovation King Mongkut’s University of Technology Thonburi Bangkok Thailand Institute of Field Robotics King Mongkut’s University of Technology Thonburi Thonburi Thailand DEVCOM Army Research Laboratory Humans in Complex Systems Division AdelphiMD United States Chula Neuroscience Center King Chulalongkorn Memorial Hospital Thai Red Cross Society Bangkok10330 Thailand Cognitive Clinical and Computational Neuroscience Department of Internal Medicine Faculty of Medicine Chulalongkorn University Bangkok10330 Thailand Department of Cognitive Sciences University of California IrvineCA United States Department of Biomedical Engineering University of California IrvineCA United States Department of Computer Engineering King Mongkut’s University of Technology Thonburi Bangkok10600 Thailand

ISBN: (纸本)9789819632930

EEG hyperscanning provides novel insights into inter-brain connectivity during social interactions by enabling the simultaneous recording of neural activity from multiple individuals. This research aims to develop and validate a new protocol in which dyads engage in a synchronized button-pressing task across both same-location and multi-location setups. Our findings reveal significantly higher interpersonal neural synchronization during the interaction period compared to the baseline. Notably, the increased neural synchronization is comparable across the same- and multi-location setups, spanning frontal, central, and posterior electrodes. Interestingly, the level of synchronization in the multi-location setup is greater than in the same-location setup over electrodes positioned above the right superior temporal gyrus (STG), a region associated with social cognition and the mirror neuron system (MNS). These findings validate our methodology for studies across different locations and open new avenues for research into inter-brain synchronization in remote environments. Our experimental protocol could enhance the design of experiments and applications involving social interaction, particularly in remote settings, which have gained popularity due to COVID-19. It also advances our understanding of the neural mechanisms that support social communication in the new normal era. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Economic and social effects

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Assessing the Influence of a CADx Scheme on Radiologists’ Analysis of Breast Nodules in Digital Mammography Using Specialized Feedback Software

Assessing the Influence of a CADx Scheme on Radiologists’ A...

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18th international Joint conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2025

作者： Schiabel, Homero Cardoso, Fernanda J. F. Palotti, Joyce M. São Carlos School of Engineering University of São Paulo Dept. of Electrical and Computer Engineering Av. Trabalhador Sao-Carlense 400 SP Sao Carlos13566-590 Brazil

The study main purpose is to address the effectiveness of a computer-aided diagnosis (CADx) scheme developed to assist radiologists in evaluating nodules in digital mammography images. Unlike traditional CADe systems, which focus primarily on detection, this scheme offers interpretative support, providing additional diagnostic insights for more accurate decisions. This work presents a custom evaluation software designed to facilitate the testing of the CADx scheme influence on radiologistsopinion by allowing them to assess mammograms independently, register their initial opinions, review the CADx output, and log their final decisions. Through this software the study involved radiologists analysing mammograms before and after reviewing the CADx-generated data. The results showed a scheme positive influence on diagnostic accuracy. Radiologists who used the CADx data exhibited in average improved sensitivity and specificity rates, with an overall reduction in error rates, for the images set under investigation. Although the scheme is still a research prototype, it demonstrates strong potential for broader application in clinical practice, offering efficiency and cost-effectiveness, especially for screening operations. The procedure described in this work indicates that, despite the need for some fine-tuning, particularly in minimizing false positives, our CADx system shows promise as a supplemental diagnostic tool that could enhance radiologistsperformance. © 2025 by SCITEPRESS– science and technology Publications, Lda.

关键词： Clinical research

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Flying Together with Audio and Video: Enhancing Communication for the Hearing-Impaired Through an Emerging Closed Captioning Standard 16th

Flying Together with Audio and Video: Enhancing Communicat...

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16th international conference on Social Robotics, ICSR + InnoBiz 2024

作者： Mou, Luntian Li, Peize Zhao, Haiwu Fu, Qiang Luo, Hong Liu, Cong Ma, Nan Huang, Tiejun Gao, Wen Beijing University of Technology Beijing China Beijing Institute of Artificial Intelligence Beijing China Shanghai University of Engineering Science Shanghai China Photosynthetic AI Tech Co. Ltd. Hangzhou China China Mobile Information Technology Co. Ltd. Hangzhou China IFLYTEK Research Hefei China Peking University Beijing China Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9789819611508

As the text-based visual representation of a program’s audio elements, Closed Captioning primarily serves as a technology to enhance communication for the hearing impaired. Since text is much simpler than audio and video, Closed Captioning is traditionally transmitted as supplementary or auxiliary information as part of the image or in an extended or private data field of an encoded video bitstream called video elementary stream, usually accompanied by one or more audio elementary streams. Since Closed Captioning is extremely important for the accessibility of the audio content of a program to the hearing impaired, we propose to encode the closed caption into a bitstream called caption elementary stream, which can fly together with audio and video elementary streams. In other words, closed caption can be stored and transmitted in a manner similar to how audio and video are handled. We have drafted a national standard for Closed Captioning in China, which is now in its final stage of approval and publication. In this paper, the main technical content of the emerging Closed Captioning standard will be introduced. Specifically, the encoding, storage, and transmission of Closed Captioning will be described. Moreover, the decoding and presentation of Closed Captioning under the two scenarios of on demand streaming and live streaming will also be designed and discussed. The AI technology of Speech-to-Text enables Closed Captioning to be implemented efficiently with the help of manual proofreading. Positively, the emergence of the Closed Captioning standard will enhance accessibility to audio-visual programs on both the broadcasting network and the Internet for the hearing-impaired in China and worldwide. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Audio streaming

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Generating Realistic Cyber Security Datasets for IoT Networks with Diverse Complex Network Properties

Generating Realistic Cyber Security Datasets for IoT Network...

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10th international conference on Internet of Things, Big Data and Security, IoTBDS 2025

作者： Al Tfaily, Fouad Ghalmane, Zakariya Termos, Mortada Brahmia, Mohamed-El-Amine Jaber, Ali Zghal, Mourad CESI LINEACT UR 7527 Strasbourg France Computer Science Department Faculty of Sciences Lebanese University Beirut Lebanon

ISBN: (纸本)9789897587504

In the cybersecurity community, finding suitable datasets for evaluating Intrusion Detection Systems (IDS) is a challenge, particularly due to limited diversity in complex network properties. This paper proposes a dual-purpose approach that generates diverse datasets while producing efficient, compact versions that maintain detection accuracy. Our approach employs three techniques - community mixing modification, centrality-based modification, and time-based modification - each targeting specific network property adjustments while achieving significant dataset size reductions (up to 81.5%). Our approach is validated on real-world datasets, including NF-UQ-NIDS, CCD-INID-V1, and TON-IoT, demonstrating its ability to generate realistic datasets while preserving network properties, attack patterns, and structural integrity. The generated datasets exhibit diverse complex network properties, making them particularly useful for IDS technique evaluation that incorporates complex network measures. The reduced size and preserved accuracy (96.4%) make these datasets especially valuable for resource-constrained environments. Moreover, our approach facilitates the construction of homogeneous datasets required for federated learning situations where data distribution similarity across clients is essential. This contribution helps address both dataset scarcity and computational efficiency challenges while ensuring that the generated datasets retain the characteristics of real-world network traffic. Copyright © 2025 by SCITEPRESS - science and technology Publications, Lda.

关键词： Federated learning

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Hybrid Graph Representation Learning: Integrating Euclidean and Hyperbolic Space 27th

Hybrid Graph Representation Learning: Integrating Euclidean ...

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27th international conference on Pattern Recognition, ICPR 2024

作者： Li, Lening Luo, Lei Sun, Yanguang Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9783031781889

Graph representation learning aims to capture the structural and relational information in graphs. Recently, Euclidean space-based methods have achieved tremendous success. However, Euclidean space exhibits structural distortion problems when modeling graph data with tree structures or hierarchy, limiting the model’s performance. Based on this, researchers introduce Hyperbolic space to preserve the original structural information, but computations in Hyperbolic space rely on inverse trigonometric functions, resulting in increased computational complexity. How to learn in multi-spaces and make use of their advantages deserves careful consideration. This paper proposes a Hybrid Graph Representation Learning (HGRL) model that trains in the Hyperbolic and Euclidean spaces jointly. Euclidean space possesses the ability to learn regular geometric and has efficient computations, while Hyperbolic spaces are better suited for representing hieranrchical and non-linear relationships. Technically, we utilize the Euclidean contrast loss to minimize distances between similar samples, helping tight clusters in the traditional space. Simultaneously, the Hyperbolic hierarchy loss and Hyperbolic uniformity loss enable the model to comprehend intricate hierarchical relationships and ensure a uniform distribution of the data on the Poincaré Ball. Extensive experiments in node classification, clustering, and visualization tasks demonstrate the effectiveness of the HGRL mode in capturing hierarchy structures. We also employed ablation studies to validate the indispensability of each component. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Contrastive Learning

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SPK: Semantic and Positional Knowledge for Zero-Shot Referring Expression Comprehension 27th

SPK: Semantic and Positional Knowledge for Zero-Shot Refer...

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27th international conference on Pattern Recognition, ICPR 2024

作者： Du, Zetao Yang, Jianhua Wang, Junbo Huang, Yan Wang, Liang School of Information Science and Technology Shanghaitech University Shanghai201210 China Beijing China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China School of Software Northwestern Polytechnical University Xi’an China

ISBN: (纸本)9783031781124

Referring expression comprehension aims to localize an object in an image based on a natural language expression. This task is challenging due to the scarcity of large-scale annotated data, which prompts the research of zero-shot methods. In zero-shot scenarios, while existing models excel at grounding, they struggle to identify the target described by textual query due to the presence of multiple objects in a scene, as well as various spatial and attribute information. To address these issues, we propose a method called Semantic and Positional Knowledge (SPK), which leverages multimodal knowledge for fine-grained cross-modal matching in the referring expression comprehension task. Specifically, we pair words with visual representations as multimodal knowledge to match the information of expressions and images, such as objects, attributes, and spatial information. This method can be directly integrated with existing multimodal grounding models for further performance improvement. Experiments on the RefCOCO/+/g datasets demonstrate the effectiveness of our method, which can obtain consistent improvements. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Semantics

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LogYourEatingHabits: A Dietary App Focusing on Eating Habits that Promotes Healthy Lifestyles

LogYourEatingHabits: A Dietary App Focusing on Eating Habits...

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11th international conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2025

作者： Toaha, Mohammad Safiul Alam Bong, Way Kiat Department of Computer Science OsloMet Oslo Metropolitan University Pilestredet 35 Oslo Norway

ISBN: (纸本)9789897587436

Maintaining healthy eating habits is essential for the overall health and well-being across all ages. While mobile dietary applications offer assistance, their complexity of meal logging and often poor design limit widespread adoption. This study presents the development of a mobile application, named LogYourEatingHabits, which is designed to simplify meal logging and emphasize both meal content and eating patterns. Emphasis was also placed on ensuring high usability and accessibility in the application, making it usable by as many user groups as possible. Using a user-centered design approach, the application was iteratively developed and improved throughout feedback from 16 participants over five iterations. Each iteration provided new insights, leading to enhancements such as more consistent design and interaction of user interfaces, and increased intuitiveness and user-friendliness. The System Usability Scale (SUS) scores showed improvements across iterations, and together with observation and interview findings, they indicated overall high perceived usability. Future works include expanding the food database, optimizing the image recognition feature and providing personalized feedback based on data gathered within the app. Copyright © 2025 by SCITEPRESS - science and technology Publications, Lda.

关键词： User centered design

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ID-RWKV: Image Deraining RWKV

ID-RWKV: Image Deraining RWKV

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2025 IEEE international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Yang, Yong Yang, Jiaxuan Huang, Shuying School of Computer Science and Technology Tiangong University Tianjin China School of Software Tiangong University Tianjin China

ISBN: (纸本)9798350368741

Although Transformer has achieved considerable results in image deraining tasks, the quadratic complexity of self-attention in this structure limits its ability to process high-resolution rainy images. The Receptance Weighted Key Value (RWKV) in the field of natural language processing (NLP) solves the expensive computational cost of self-attention in Transformers by using linear computational complexity to learn long-range dependencies of features. Based on advanced design of RWKV, we propose an image deraining RWKV (ID-RWKV) that gradually obtains fine rainless images by constructing multiple deraining stages. At each stage, a U-shaped rain removal network (U-RRNet) is constructed to encode and decode image features, and output the rain removal results for the current stage. Each layer of U-RRNet consists of Fourier enhancement module (FFM) and local-global RWKV Block (LGRB). FEM is constructed to extract and enhance the features in the frequency domain. LGRB is designed based on RWKV structure to improve the performance and efficiency of deraining models. To better learn local and global contextual information, we propose a LG-WKV attention mechanism to enhance local and global dependencies. To reduce the loss of background information and increase the stability of the network, we construct a deep-shallow feature fusion module (DSFFM) to supplement shallow features. Following extensive experimentation, we demonstrate that our method not only outperforms the current state-of-the-art methods, but also requires fewer parameters and less computation than the Transformer-based method. © 2025 IEEE.

关键词： deep-shallow feature fusion image deraining RWKV

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Towards Maximizing Semantic Coverage for Image-Text Retrieval

Towards Maximizing Semantic Coverage for Image-Text Retrieva...

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international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Junhao Xu Zheng Liu Zhumin Chen Fei Shen School of Computer Science and Technology Shandong University China School of Computer Science and Technology Shandong University of Finance and Economics China School of Computer Science and Engineering Nanjing University of Science and Technology China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

To establish semantic associations between images and texts, existing Image-Text Retrieval (ITR) methods primarily focus on fixed-scale fragments, which only identify explicit semantic categories. Consequently, semantic coverage is constrained, leading to the omission of certain semantic associations. To enlarge the semantic coverage, we propose the Semantic Coverage-Aware Network (SCA-Net). First, explicit semantic categories are identified by SCA-Net through analyzing the semantic membership of visual and textual fragments, thereby establishing more precise explicit semantic associations. Second, implicit semantic categories are identified by SCA-Net via adaptively aggregating visual and textual fragments across various scales using a co-occurrence-aware router, thereby significantly expanding the semantic coverage and establishing complete semantic associations. Third, image-text similarity is calculated using the attention mechanism over a broader range of semantic coverage. Extensive experiments demonstrate that SCA-Net significantly enhances ITR performance compared to state-of-the-art methods by maximizing semantic coverage.

关键词： Visualization Attention mechanisms Aggregates Semantics Signal processing Acoustics Speech processing Cross modal retrieval

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