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  1. 261

    A review: Multi-Objective Algorithm for Community Detection in Complex Social Networks by Mariwan Wahid Ahmed, Kamaran Faraj

    Published 2025-02-01
    “…Which are analyzed by 15 different approaches in order to choose from works published during the period 2019–2024. These strengths and limitations of various MOAs are reviewed with a comparative analysis to provide insights into both the effectiveness and computational efficiency of these methods. …”
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    A lightweight and explainable CNN model for empowering plant disease diagnosis by Chiranjit Pal, Swastik Karmakar, Imon Mukherjee, Partha Pratim Chakrabarti

    Published 2025-08-01
    “…The cross-domain validation rate (CDVR) is computed to assess its cross-domain adaptability, with the model showing competitive results compared to other pre-trained models. …”
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  4. 264

    A systematic review of data and models for predicting food flavor and texture by Michael Gunning, Ilias Tagkopoulos

    Published 2025-01-01
    “…Texture prediction has seen comparatively less research interest but may prove to be impactful in food quality control pipelines, although more work is needed in creating robust food texture datasets. …”
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  5. 265

    Intent-driven network automation through sustainable multimodal generative AI by Kostis Trantzas, Dimitrios Brodimas, Besiana Agko, Georgios Christos Tziavas, Christos Tranoris, Spyros Denazis, Alexios Birbas

    Published 2025-06-01
    “…Therefore, several state-of-the-art online and locally deployed models are compared. The ultimate motivation of this work is to validate the feasibility and accuracy of the proposed framework, promoting sustainability through minimal resource consumption and cost efficiency. …”
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  6. 266

    Unraveling the Nexus of ML and 6G: Challenges, Opportunities, and Future Directions by Mohammed Anis Oukebdane, A. F. M. Shahen Shah, Abul Kalam Azad, John Ekoru, Milka Madahana

    Published 2025-01-01
    “…Researchers and professionals aiming to create strong, ML-driven wireless infrastructures beyond 5G find basic reference in this work.…”
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    Performance Evaluation of YOLOv11 and YOLOv12 Deep Learning Architectures for Automated Detection and Classification of Immature Macauba (<i>Acrocomia aculeata</i>) Fruits by David Ribeiro, Dennis Tavares, Eduardo Tiradentes, Fabio Santos, Demostenes Rodriguez

    Published 2025-07-01
    “…The public release of the VIC01 dataset and trained weights ensures reproducibility and supports future research. Our results underscore the importance of selecting architectures based on application-specific requirements, balancing detection accuracy, background discrimination, and computational constraints. …”
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    A depth-wise separable VGG19-capsule network for enhanced bell pepper and grape leaf disease classification with ensemble activation by Midhun P Mathew, Sudheep Elayidom, Jagathy Raj V P, Abubeker K M

    Published 2025-01-01
    “…The proposed VGG19-CapsNet framework is developed and deployed in a 128-core Jetson Nano single-board computer with graphics processing support. The research outcomes set a benchmark for accuracy and present a paradigm shift in automated leaf disease classification. …”
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    DBN Classifier for Classification of Benign and Malignant Solitary Pulmonary Nodule by LIU Lu, YANG Pei-liang, SUN Wei-wei, ZHOU Yang, ZHAO Hong-yuan

    Published 2018-06-01
    “…Before this team work,768 dimensional feature space is obtained by multi-resolution histograms of SPN image. …”
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    mindLAMPVis as a Co-Designed Clinician-Facing Data Visualization Portal to Integrate Clinical Observations From Digital Phenotyping in Schizophrenia: User-Centered Design Process a... by Karthik Sama, Jaya Sreevalsan-Nair, Soumya Choudhary, Srilakshmi Nagendra, Preethi V Reddy, Asher Cohen, Urvakhsh Meherwan Mehta, John Torous

    Published 2025-06-01
    “…This paper explores the process of creating a novel data visualization system for a digital mental health app and outlines the necessary steps in the process. This work demonstrates co-design involving collaboration between teams across geographies and disciplines based on clinicians’ requirements. …”
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