Polarimetric SAR Ship Detection Using Context Aggregation Network Enhanced by Local and Edge Component Characteristics by Canbin Hu, Hongyun Chen, Xiaokun Sun, Fei Ma

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Classification of ROI-based fMRI data in short-term memory tasks using discriminant analysis and neural networks by Magdalena Fafrowicz, Marcin Tutajewski, Igor Sieradzki, Jeremi K. Ochab, Jeremi K. Ochab, Anna Ceglarek-Sroka, Koryna Lewandowska, Tadeusz Marek, Barbara Sikora-Wachowicz, Igor T. Podolak, Paweł Oświęcimka, Paweł Oświęcimka, Paweł Oświęcimka

“…The presented results reveal the benefits of applying machine learning algorithms to investigate working memory dynamics.…”
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Artificial intelligence in neuroimaging: Opportunities and ethical challenges by Neha Brahma, S. Vimal

“…The integration of artificial intelligence (AI) into neuroimaging represents a transformative shift in the diagnosis and treatment of neurodegenerative diseases. AI algorithms, particularly deep learning models, have demonstrated remarkable capabilities in analyzing complex neuroimaging data, leading to enhanced diagnostic accuracy and personalized treatment strategies. …”
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Proposed Comprehensive Methodology Integrated with Explainable Artificial Intelligence for Prediction of Possible Biomarkers in Metabolomics Panel of Plasma Samples for Breast Canc... by Cemil Colak, Fatma Hilal Yagin, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

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Network intrusion detection model using wrapper based feature selection and multi head attention transformers by Muhammad Umer, Muhammad Tahir, Muhammad Sardaraz, Muhammad Sharif, Hela Elmannai, Abeer D. Algarni

“…Many researchers have worked to address the problem of intrusion detection in networks. Machine learning and deep learning have also been used. …”
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Utilizing UAV and orthophoto data with bathymetric LiDAR in google earth engine for coastal cliff degradation assessment by Paweł Tysiąc, Rafał Ossowski, Łukasz Janowski, Damian Moskalewicz

“…Abstract This study introduces a novel methodology for estimating and analysing coastal cliff degradation, using machine learning and remote sensing data. Degradation refers to both natural abrasive processes and damage to coastal reinforcement structures caused by natural events. …”
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Detection and monitoring of Melampsora spp. Damage in multiclonal poplar plantations coupling biophysical models and Sentinel-2 time series by Carlos Camino, Alexey Valero-Jorge, Erika García Lima, Ramón Álvarez, Pieter S.A. Beck, Flor Álvarez-Taboada

“…In this study, we developed three machine learning (ML) detection models (DMs) for identifying rust-affected poplar trees coupling Sentinel-2 time series and the PROSAIL radiative transfer model. …”
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LSTM-JSO framework for privacy preserving adaptive intrusion detection in federated IoT networks by Shaymaa E. Sorour, Mohammed Aljaafari, Amany M. Shaker, Ahmed E. Amin

“…A Long Short-Term Memory (LSTM)-based architecture accurately captures complex intrusion patterns. Federated learning is leveraged to enable collaborative model training across multiple IoT networks while maintaining data privacy and reducing vulnerability to data poisoning. …”
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A cooperative intrusion detection system for internet of things using fuzzy logic and ensemble of convolutional neural networks by Xiongwei Qiu, Lianzhi Shi, Pengtong Fan

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Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sl... by Yasmine M Mohamed, José Mancera, Andreas Brandenberg, Stefan Fischli, Michael M Havranek

“…Machine learning (ML) models were built using a tree-based ensemble algorithm to detect hypoglycemic events registered by CGMS. …”
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Identification of immune-associated biomarkers in diagnosing allergic rhinitis by Qi Cheng, PhD, Jie Fei, MS, Yuanfen Liao, MS, Hang Lin, MD, Yubao Cui, PhD

“…Additionally, 5 machine-learning algorithms were integrated to screen for novel diagnostic biomarkers for AR. …”
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Deep convolutional neural network (DCNN)-based model for pneumonia detection using chest x-ray images by S. I. Ele, U. R. Alo, H. F. Nweke, A. H. Okemiri, E. O. Uche-Nwachi

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Development of an Automated Crack Detection System for Port Quay Walls Using a Small General-Purpose Drone and Orthophotos by Daiki Komi, Daisuke Yoshida, Tomohito Kameyama

“…The system employs the YOLOR (You Only Learn One Representation) object detection algorithm, enhanced by two novel image processing techniques—overlapping tiling and pseudo-altitude slicing—to overcome the resolution limitations of low-cost cameras. …”
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Remote Sensing Tools for Monitoring Marine Phanerogams: A Review of Sentinel and Landsat Applications by Noelia Campillo-Tamarit, Juan Víctor Molner, Juan M. Soria

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Linear regressive weighted Gaussian kernel liquid neural network for brain tumor disease prediction using time series data by Firoz Khan, Sardar Irfanullah Amanullah, Shitharth Selvarajan

“…Following data collection, preprocessing is performed, involving two key processes: handling missing data and outlier detection. …”
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Sensor-Based Yield Prediction in Durum Wheat Under Semi-Arid Conditions Using Machine Learning Across Zadoks Growth Stages by Süreyya Betül Rufaioğlu, Ali Volkan Bilgili, Erdinç Savaşlı, İrfan Özberk, Salih Aydemir, Amjad Mohamed Ismael, Yunus Kaya, João P. Matos-Carvalho

“…Five different machine learning algorithms (Random Forest, Gradient Boosting, AdaBoost, LightGBM, and XGBoost) were tested individually for each stage, and the model performances were evaluated using statistical metrics such as R²%, RMSE t/ha, and MAE t/ha. …”
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Developing a Multisensor-Based Machine Learning Technology (Aidar Decompensation Index) for Real-Time Automated Detection of Post–COVID-19 Condition: Protocol for an Observational... by Jenny Mathew, Jaclyn A Pagliaro, Sathyanarayanan Elumalai, Lauren K Wash, Ka Ly, Alison J Leibowitz, Varsha G Vimalananda

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Multi-Signal Induction Motor Broken Rotor Bar Detection Based on Merged Convolutional Neural Network by Tianyi Wang, Shiguang Wen, Shaotong Sheng, Huimin Ma

“…This method combines advanced signal processing techniques and deep learning algorithms to provide a practical solution for motor broken rotor bar detection.…”
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Effects of data transformation and model selection on feature importance in microbiome classification data by Zuzanna Karwowska, Oliver Aasmets, Estonian Biobank research team, Tomasz Kosciolek, Elin Org

“…However, while different transformations resulted in comparable classification performance, the most important features varied significantly, which highlights the need to reevaluate machine learning–based biomarker detection. Conclusions Microbiome data transformations can significantly influence feature selection but have a limited effect on classification accuracy. …”
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Automatic license-plate recognition by A. V. Poltavskii, T. G. Yurushkina, M. V. Yurushkin

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