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An Automated Framework of Superpixels-Saliency Map and Gated Recurrent Unit Deep Convolutional Neural Network for Land Cover and Crops Disease Classification

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IEEE Access 2025年 13卷 76370-76387页

作者： Haider, Irfan Khan, Muhammad Attique Nazir, Muhammad Masood, Saleha Kraiem, Naoufel Abdulaziz Alhammadi, Dina HITEC University Department of Computer Science Taxila47080 Pakistan Prince Mohammad Bin Fahd University College of Computer Engineering and Science Department of Artificial Intelligence Dhahran34754 Saudi Arabia King Fahd University of Petroleum and Minerals IRC for Finance and Digital Economy Dhahran31261 Saudi Arabia King Khalid University College of Computer Science Abha61413 Saudi Arabia Princess Nourah bint Abdulrahman University College of Computer and Information Sciences Department of Information Systems P.O.Box 84428 Riyadh11671 Saudi Arabia

In this work, we proposed an automated deep learning and saliency map architecture for the segmentation of crops, leaf disease segmentation, and land cover classification. The proposed framework is based on two embedded steps. In the first step, crop leaf disease segmentation was performed using superpixel clustering-based saliency maps and Bayesian optimization. The contrast enhancement technique is designed in the first segmentation phase and is passed to the saliency technique for the disease segmentation. In the second phase, EfficientNet-b0 architecture is fine-tuned with hyperparameters optimized via Bayesian Optimization. Also, the fine-tuned model is embedded with a single self-attention residual block fused with an efficient average pool layer. Training has been performed on segmented and contrast-enhanced images that were later fused using a serial-embedded approach. The extracted features in the testing phase are further optimized using the modified moth flame-controlled bisection (MFcB) technique. Finally, the extracted features are classified using machine learning classifiers for the final classification. Experiments are performed on the publically available cucumber leaf dataset and Remote sensing dataset with an improved accuracy of 97.6% and 92.90%, respectively. A comparison with state-of-the-art techniques shows that the proposed architecture has improved performance. © 2013 IEEE.

关键词： Superpixels

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A Social Robot Companion for Individuals Eating Alone 25

A Social Robot Companion for Individuals Eating Alone

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30th International Conference on Intelligent User Interfaces Companion, IUI 2025

作者： Soufargi, Selim Niewiadomski, Radoslaw Fong, Hunter Mancini, Maurizio Department of Computer Science Sapienza University of Rome Rome Italy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy

ISBN: (纸本)9798400714092

In this paper, we present the first implementation of a social robot acting as a companion for individuals eating alone. Our system can engage in multimodal interactions with the user during meals. It conducts conversations on various topics, complemented by gestures and other nonverbal behaviors. The system comprises a NAO robot, human activity recognition modules, a speech recognition module, and a dialog management system integrated with an LLM model. In the paper, we present a technical description of the system and the interaction flow, as well as discuss the possible applications and planned validation. © 2025 Copyright held by the owner/author(s).

关键词： Social robots

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The Intersection of Genetics and Neuroimaging: A Systematic Review of Imaging Genetics in Neurological Disease for Personalized Treatment

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Journal of Molecular Neuroscience 2025年第2期75卷 1-26页

作者： Mashhour, Mahinaz A. Youssef, Ibrahim Wahed, Manal Abdel Mabrouk, Mai S. Biomedical Engineering Department Misr University for Science and Technology Giza Egypt Systems and Biomedical Engineering Department Cairo University Giza Egypt Center for Informatics Science (CIS) School of Information Technology and Computer Science Nile University Giza Egypt

Imaging genetics is one of the important keys to precision medicine that leads to personalized treatment based on a patient’s genetics, phenotype, or psychosocial characteristics. It deepens the understanding of the mechanisms through which genetic variations contribute to neurological and psychiatric disorders. This systematic review overviews the methods and applications of imaging genetics in the context of neurological diseases, mentioning its potential role in personalized medicine. Following PRISMA guidelines, this review systematically analyzes 28 studies integrating genetic and neuroimaging data to explore disease mechanisms and their implications for precision medicine. Selected research included multiple neurological disorders, including frontotemporal dementia, Alzheimer’s disease, bipolar disorder, schizophrenia, Parkinson’s disease, and others. Voxel-based morphometry was the most common imaging technique, while frequently examined genetic variants included APOE, C9orf72, MAPT, GRN, COMT, and BDNF. Associations between these variants and regional gray matter loss (e.g., frontal, temporal, or subcortical regions) suggest that genetic risk factors play a key role in disease pathophysiology. Integrating genetic and neuroimaging analyses enhances our understanding of disease mechanisms and supports advancements in precision medicine. © The Author(s) 2025.

关键词： Imaging genetics Neurological diseases Precision medicine Radiogenomics Voxel-based morphometry

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Advanced Air Mobility: Innovations, Applications, Challenges, and Future Potential

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Journal of Air Transportation 2025年第2期33卷 169-187页

作者： Raza, Waleed Renkhoff, Justus Ogirimah, Olayemi Bawa, Gurvir Kaur Stansbury, Richard S. Department of Electrical Engineering and Computer Science Embry-Riddle Aeronautical University Daytona BeachFL32114 United States Department of Information Systems University of Maryland BaltimoreMD21250 United States

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Advancements in Efficient Underwater Image Restoration Using ETransMapNet for Enhanced Dehazing

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Tehnicki Vjesnik 2025年第3期32卷 1125-1132页

作者： Indumathi, C.P. Alshahrani, Haya Mesfer N.A., Natraj C.H., Sarada Devi Department of Computer Science and Engineering University College of Engineering BIT Campus Anna University Tamilnadu Tiruchirapalli24 India Department of Information Systems College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Maharashtra Pune India Department of CSE Meenakshi College of Engineering India

Underwater (UW) information is essential for advancing human exploration and utilization of the underwater world, including fields such as UW Paleology, UW Target Detection, UW Object Tracking, UW Surveillance, and related activities. Visual media like movies and images enhance our natural understanding of underwater objectives. In the past decade, underwater photo restoration and enhancement have gained increasing attention. This study proposes a novel approach employing the recently developed Convolutional Neural Network (CNN) for dehazing, named ETransMapNet (Efficient Transmission Map Network). ETransMapNet is designed with convolution layers and nonlinear activations to execute four sequential processes: nonlinear regression, local maxima detection, multi-scale decomposition, and convolutional feature extraction. Unlike traditional CNNs, ETransMapNet replaces the initial layer's Rectified Linear Unit (ReLU) activation with a convolution layer utilizing a Maxout activation function. ETransMapNet extracts features using three convolution kernels of different sizes (3 × 3, 5 × 5, and 7 × 7). The method suppresses noise in the estimated transmittance map, while local extremum values maintain local consistency within the transmittance map. This study adopts Bilateral ReLU (BReLU) for normalizing network outputs within a 0 to 1 range. Additionally, Adaptive Bilateral Filtering (ABF) is applied to remove redundant artifacts from the predicted transmission map. White balancing addresses color divergence, and Laplacian pyramid fusion combines the color-corrected and dehazed images. In the final stage, the resultant image is transformed into the Wavelet and Directional Filter Banks (WDFB) domain for denoising and edge enhancement. Performance metrics reveal that the proposed ETransMapNet approach improves performance by 38%-50% compared to previous methods. © 2025, Strojarski Facultet. All rights reserved.

关键词： Underwater photography

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An Extended Euclidean Algorithm Implementation over Ciphertext Space 2nd

An Extended Euclidean Algorithm Implementation over Ciphert...

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2nd International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications, SITAIBA 2023

作者： Chi, Po-Wen Lin, Yuan-Pang Wang, Ming-Hung Chuang, Yun-Hsin Department of Computer Science and Information Engineering National Taiwan Normal University Taiwan Taipei Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Taiwan Chiayi Taiwan Engineering Management Graduate Program College of Engineering National Cheng Kung University Taiwan Tainan Taiwan

ISBN: (纸本)9789819777853

Fully homomorphic encryption (FHE) is a useful cryptographic primitive. It makes a third-party manipulate data in the ciphertext space and therefore is a key technology for privacy-preserving outsourcing services. Theoretically, FHE can evaluate any circuits. However, the implementation is not trivial. The reason it lacks lots of basic operations like conditional check and branch control. In this paper, we focus on extended Euclidean algorithm operation over FHE. We introduce the problems we encounter and show how we solve these issues. We implement our design and evaluate its performance on a real computer. Finally, we propose some research directions for our future work. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ciphertext

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Applications of Topological Data Analysis with Morphology Operators on Hypergraphs

Applications of Topological Data Analysis with Morphology Op...

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International Conference on Mathematics of Intelligent Computing and Data science, ICMICDS 2022

作者： Ramkumar, P.B. Dhanya, P.M. Department of Mathematics Rajagiri School of Engineering and Technology Kerala Kakkanad India Department of Computer Science and Business Systems Rajagiri School of Engineering and Technology Kerala Kakkanad India

ISBN: (纸本)9789819615049

A hypergraph is a type of graph, H=(V,E) where V is the set of nodes and E is the set of hyperedges;where one edge consists of may nodes. Morphological operators are nonlinear operators which can be applied on images, graphs, hypergraphs etc. Dilation and erosion are morphological operators and other operators like opening, closing can be obtained by repeated application of these operators. Topological space consists of a set X together with topology τ defined on X, which satisfies the axioms namely Nullset, arbitrary union of opensets and finite intersection of opensets. Such a topological space S=(X,T) is compatible with a hypergraph H if X=VH∪EH where VH and EH are the vertex set and edge set respectively. The morphological operators induces several topology on hypergraph with its compatible topological space S=(X,T). Neighborhood of a node is defined in many ways which can be considered as open sets in the corresponding topological space. The purpose of this paper is to apply topological properties on hypergraphs using morphological operators. Separation axiom and closure function are illustrated using hypergraph structure. The work is extended to crime analysis, text processing and patient disease analysis. Topological feature extraction is done on Barcodes created from crime hypergraphs. This gives a better visualization of crime analysis. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Graph theory

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Mixed RF/FSO Communication systems With Rate Splitting

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IEEE Journal on Selected Areas in Communications 2025年第5期43卷 1621-1634页

作者： Zhang, Yiran Xiao, Zhichen Yang, Liang Bithas, Petros S. Hasna, Mazen O. Karagiannidis, George K. Hunan University College of Computer Science and Electronic Engineering Changsha410082 China National and Kapodistrian University of Athens Department of Digital Industry Technologies Athens157 72 Greece Qatar University Department of Electrical Engineering Doha2713 Qatar Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki541 24 Greece Artificial Intelligence and Cyber Systems Research Center Beirut0379-7751 Lebanon

In this paper, rate splitting (RS) has been applied in a mixed dual-hop radio frequency/free space optical (RF/FSO) relay system. In particular, assuming fixed-gain amplify-and-forward (AF) and decode-and-forward (DF) relay protocols, the performance of both heterodyne detection and intensity-modulated direct detection (IM-DD) has been analytically evaluated. In this framework, it is assumed that the RF channel suffers from Rayleigh fading, while the FSO channel is affected by the atmospheric turbulence-induced fading with Málaga (M) distribution and pointing errors. For the considered system, we derive expressions for the outage probability, the average bit error rate (BER), and the average channel capacity. In addition, the asymptotic performance of the system at high signal-to-noise ratios regime is analyzed, special cases are discussed, and useful insights have been extracted. Finally, numerical results are presented to verify the accuracy of the analytical and asymptotic expressions. © 1983-2012 IEEE.

关键词： Heterodyne detection

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Depth-aware Image Captioning with Bus Dataset for Visually Impaired Individuals 24

Depth-aware Image Captioning with Bus Dataset for Visually I...

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8th International Conference on computer science and Artificial Intelligence, CSAI 2024

作者： Xiang, Wang Sanqian, Li Risa, Higashita Jie, Li Hongwu, Qin Jiang, Liu Department of Electronic and Information Engineering Changchun University Changchun China Research lnstitute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

ISBN: (纸本)9798400718182

Visually impaired individuals face difficulties in public transportation, especially in recognizing bus numbers. Though existing image captioning method can provide some bus scene information via voice broadcasting, precisely recognizing bus number while analyzing complex scenes remains challenges. To overcome this bottleneck, we propose a novel Text based Depth-aware image Captioning network (TDCnet) that facilitates a deeper understanding of the spatial relationships and geometric configurations of objects within bus scenes. Specially, we first carefully construct a new real-world dataset of bus scene integrated with bus number of LED strobe effect, to ensure generality and representations in practice. Then, we incorporate the depth information into the object and optical character recognition (OCR) feature for exploiting the spatial geometric relationships and capturing high-level semantic information. Finally, the experimental results demonstrate the necessity of constructing the Buscap dataset by comparing it with the public Textcap dataset. Besides, the comparison with other competing benchmark models verifies the effectiveness and practicability of the proposed TDCnet method. © 2024 Copyright held by the owner/author(s).

关键词： Bus transportation

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"There is a Damn Hello on the Social Media!" Insights into Public Risk Communication in the Digital Age 18th

"There is a Damn Hello on the Social Media!" Insights into P...

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18th IFIP WG 11.12 International Symposium on Human Aspects of Information Security and Assurance, HAISA 2024

作者： Große, Christine Division of Computer Science Electrical and Space Engineering Department of Digital Services and Systems Luleå University of Technology Luleå971 87 Sweden

ISBN: (纸本)9783031725586

The ability to handle threats, such as disinformation, manipulation of public opinion, and disruption of critical supplies, is becoming increasingly important, thus, necessitating, among other strategies, efforts to establish a proper risk communication to the public. This paper addresses the need for more empirical research in this area to contribute to the development of an in-depth understanding of public risk communication that includes information-related threats and cyber issues. The study involves officials of three public organizations entrusted with safety and security in society: the police, the rescue service, and the county administrative board of a county in the middle of Sweden. The results detail the recognition of risks to be communicated, the organization of the communication process, the messages that these actors seek to bring forth, and to whom as well as challenges of public risk communication in the digital era. The findings indicate that information-related and cyber risks are increasingly essential to consider as an additional layer of public communication. Two implications emerged as particularly important: (1) all communication about risks and crises must consider the systemic risk of mis- and disinformation, and (2) tailored communication about the risks interrelated with disinformation should use human-centered, dialogue-based, and moderated approaches. Further research can focus on associated challenges, considering the distribution of responsibilities, inter-organizational information sharing and cooperation, and the possibly stochastic effects on critical (information) infrastructures and, ultimately, societal values. © IFIP International Federation for Information Processing 2025.

关键词： Stochastic systems

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