A Proposed Method for Deep Learning-Based Automatic Tracking with Minimal Training Data for Sports Biomechanics Research by Daichi Yamashita, Minoru Matsumoto, Takeo Matsubayashi

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Image dataset of Taro Leaf Blight disease collected from the West African Sub-RegionMendeley Data by Chidiebere Nwaneto, Chika Yinka-Banjo, Ogban-Asuquo Ugot, Obiageli Umeugochukwu, Thompson Annor

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Through the Citizen Scientists’ Eyes: Insights into Using Citizen Science with Machine Learning for Effective Identification of Unknown-Unknowns in Big Data by Kameswara Bharadwaj Mantha, Hayley Roberts, Lucy Fortson, Chris Lintott, Hugh Dickinson, William Keel, Ramanakumar Sankar, Coleman Krawczyk, Brooke Simmons, Mike Walmsley, Izzy Garland, Jason Shingirai Makechemu, Laura Trouille, Clifford Johnson

“…Although machine learning (ML) can quickly parse large data sets, it struggles to robustly identify scientifically interesting objects, a task at which humans excel. …”
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Timeseria: An object-oriented time series processing library by Stefano Alberto Russo, Giuliano Taffoni, Luca Bortolussi

“…Timeseria comes with a comprehensive set of base data structures, data transformations for resampling and aggregation, common data manipulation operations, and extensible models for data reconstruction, forecasting and anomaly detection. …”
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A reliable approach for identifying acute lymphoblastic leukemia in microscopic imaging by Mimosette Makem, Levente Tamas, Lucian Bușoniu

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MED-AGNeT: An attention-guided network of customized augmentation of samples based on conditional diffusion for textile defect detection by Jun Liu, Haolin Li, Hao Liu, Jiuzhen Liang

“…Fabric defect detection plays a vital role in ensuring the production quality of the textile manufacturing industry. …”
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A comprehensive review of deep learning approaches for rice disease detection: Datasets, methodologies, and future directions by Usman Idris Ismail, Hui Na Chua, Rosdiadee Nordin, Muhammed Kabir Ahmed

“…It also compares popular deep learning architectures, discussing their respective strengths and shortcomings in rice disease detection. Furthermore, it explores the limitations of existing models in terms of real-world deployment, including issues related to data diversity, domain adaptation, and hardware constraints. …”
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Integration of metaheuristic based feature selection with ensemble representation learning models for privacy aware cyberattack detection in IoT environments by M. Karthikeyan, R. Brindha, Maria Manuel Vianny, V. Vaitheeshwaran, Mrinal Bachute, Sanket Mishra, Bibhuti Bhusan Dash

“…Despite IoT’s merits, rising cyberthreats and the rapid growth of smart devices increase the risk of data breaches and security attacks. The increasing complexity of cyberattacks demands advanced intrusion detection systems (IDS) to defend crucial assets and data. …”
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Practical Comparison Between Genetic Algorithm and Clonal Selection Theory on KDD Dataset by Najlaa Aldabagh, Mafaz Khalil

“…The comparison to be done by applying the two models on some records of Knowledge Discovery and Data mining tools which is known by the name KDD data sets (its records the data of the interring packets to the computer system from the internet), to produce population ( in case of GA) or antibodies (in case of CST) can recognize these abnormal records.…”
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Specific PCR primer designed from genome data for rapid detection of Fusarium oxysporum f. sp. cubense tropical race 4 in the Cavendish banana. by Shunsuke Nozawa, Dan Charlie Joy Pangilinan, G Alvindia Dionisio, Kyoko Watanabe

“…The primers allowed for rapid detection in experimentally diseased tissues. We concluded that this novel primer set enables the simplified diagnosis of fusarium wilt caused by Foc TR4 in bananas.…”
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DART-Vetter: A Deep Learning Tool for Automatic Triage of Exoplanet Candidates by Stefano Fiscale, Laura Inno, Alessandra Rotundi, Angelo Ciaramella, Alessio Ferone, Christian Magliano, Luca Cacciapuoti, Veselin Kostov, Elisa V. Quintana, Giovanni Covone, Maria Teresa Muscari Tomajoli, Vito Saggese, Luca Tonietti, Antonio Vanzanella, Vincenzo Della Corte

“…We trained and tested DART-Vetter on several data sets of publicly available and homogeneously labelled TESS and Kepler light curves in order to prove the effectiveness of our model. …”
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Detection of prospective areas for mineralization deposits using image analysis technique of aeromagnetic data around Marsa Alam-Idfu road, Eastern Desert, Egypt by A.S.M. Assran, R.A.Y. El Qassas, M.H.M. Yousef

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A Comprehensive Drift-Adaptive Framework for Sustaining Model Performance in COVID-19 Detection From Dynamic Cough Audio Data: Model Development and Validation by Theofanis Ganitidis, Maria Athanasiou, Konstantinos Mitsis, Konstantia Zarkogianni, Konstantina S Nikita

“… BackgroundThe COVID-19 pandemic has highlighted the need for robust and adaptable diagnostic tools capable of detecting the disease from diverse and continuously evolving data sources. …”
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Deployable Deep Learning for Cross-Domain Plant Leaf Disease Detection via Ensemble Learning, Knowledge Distillation, and Quantization by Mohammad Junayed Hasan, Suvodeep Mazumdar, Sifat Momen

“…We propose a unified optimization approach integrating ensemble learning, knowledge distillation, and quantization across 24 deep learning architectures for edge-compatible disease detection. Strategic data augmentation and ADASYN-based balancing mitigate the severe 75:1 class imbalance, while systematic hyperparameter tuning optimizes model configurations. …”
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Uncertainty CNNs: A path to enhanced medical image classification performance by Vasileios E. Papageorgiou, Georgios Petmezas, Pantelis Dogoulis, Maxime Cordy, Nicos Maglaveras

“…The automated detection of tumors using medical imaging data has garnered significant attention over the past decade due to the critical need for early and accurate diagnoses. …”
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An Integrated Framework for Supplementing Online Water Quality Monitoring in the Detection of Contamination Events in Water Distribution Networks by Camilo Salcedo, Dominic L. Boccelli

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SMArt Retro study: a retrospective data analysis of the Russian registry of patients with spinal muscular atrophy by D. V. Vlodavets, O. A. Shchagina, A. V. Polyakov, S. I. Kutsev

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Quantification of tuberculosis exposure in a high-burdened setting by Benjamin Patterson, Sabine Hermans, Robin Wood, Frank Cobelens

“…Abstract Recent studies using sensitive aerosol sampling and detection methodologies, have enumerated aerosolized Mycobacterium tuberculosis (Mtb) across a spectrum of tuberculosis states in a high-burdened setting. …”
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An AI-Driven Cybersecurity Framework for IoT: Integrating LSTM-Based Anomaly Detection, Reinforcement Learning, and Post-Quantum Encryption by Mozamel M. Saeed

“…This study proposes a unified AI-driven cybersecurity framework to detect anomalies, verify data integrity, automate incident response, and ensure long-term cryptographic resilience. …”
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An Accurate Deep Learning-Based Computer-Aided Diagnosis System for Gastrointestinal Disease Detection Using Wireless Capsule Endoscopy Image Analysis by Sameh Abd El-Ghany, Mahmood A. Mahmood, A. A. Abd El-Aziz

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