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Physics-informed features in supervised machine learning

• Authors : Lampani, Margherita; Guastavino, Sabrina; Piana, Michele

Subjects: Statistics - Machine Learning; Computer Science - Machine Learning; Mathematics - Numerical Analysis

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A Practical Approach to using Supervised Machine Learning Models to Classify Aviation Safety Occurrences

• Authors : Siow, Bryan Y.

Subjects: Computer Science - Machine Learning; Computer Science - Artificial Intelligence; I.2.6

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Earthquake Declustering Using Supervised Machine Learning

• Authors : Shcherbakov, Robert; Kothari, Sidhanth

Subjects: Physics - Geophysics

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Using Satellite Images And Self-supervised Machine Learning Networks To Detect Water Hidden Under Vegetation

• Authors : Iakovidis, Ioannis; Kalantari, Zahra; Payberah, Amir Hossein

Subjects: Computer Science - Computer Vision and Pattern Recognition

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Supervised machine learning based signal demodulation in chaotic communications

• Authors : Kozlenko, Mykola

Subjects: Electrical Engineering and Systems Science - Signal Processing; Computer Science - Machine Learning; 68T07 (Primary) 94A12, 94A13, 94A14 (Secondary)

• Source: 2022 International Conference on Innovative Solutions in Software Engineering (ICISSE), Vasyl Stefanyk Precarpathian National University, Ivano-Frankivsk, Ukraine, Nov. 29-30, 2022, pp. 313-317

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Enhancing Sensitivity for Di-Higgs Boson Searches Using Anomaly Detection and Supervised Machine Learning Techniques

• Authors : Chekanov, Sergei V.; Islam, Wasikul; Luongo, Nicholas

Subjects: High Energy Physics - Phenomenology

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Improving User Behavior Prediction: Leveraging Annotator Metadata in Supervised Machine Learning Models

• Authors : Ng, Lynnette Hui Xian; Jaidka, Kokil; Tay, Kaiyuan

Subjects: Computer Science - Machine Learning; Computer Science - Artificial Intelligence

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Development and Application of Self-Supervised Machine Learning for Smoke Plume and Active Fire Identification from the FIREX-AQ Datasets

• Authors : LaHaye, Nicholas; Easley, Anistasija; Yun, Kyongsik

Subjects: Computer Science - Machine Learning; Computer Science - Artificial Intelligence; Computer Science - Computer Vision and Pattern Recognition

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The VMC Survey : LI. Classifying extragalactic sources using a probabilistic random forest supervised machine learning algorithm

• Authors : Pennock, Clara M.; van Loon, Jacco Th.; Cioni, Maria-Rosa L.

Subjects: Astrophysics - Astrophysics of Galaxies

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Evaluation of (Un-)Supervised Machine Learning Methods for GNSS Interference Classification with Real-World Data Discrepancies

• Authors : Heublein, Lucas; Raichur, Nisha L.; Feigl, Tobias

Subjects: Computer Science - Computer Vision and Pattern Recognition; Computer Science - Machine Learning; 68-00, 68T01, 68T30

• Source: Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+), Baltimore, Maryland, September 2024, pp. 1260-1293

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