Depth-specific soil moisture estimation in vegetated corn fields using a canopy-informed model: A fusion of RGB-thermal drone data and machine learning by Milad Vahidi, Sanaz Shafian, William Hunter Frame

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A comparative study of machine learning algorithms for fall detection in technology-based healthcare system: Analyzing SVM, KNN, decision tree, random forest, LSTM, and CNN by Afuan Lasmedi, Isnanto R. Rizal

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Single-cell RNA-sequencing and genome-wide Mendelian randomisation along with abundant machine learning methods identify a novel B cells signature in gastric cancer by Qi Ma, Jie Gao, Yuan Hui, Zhi-Ming Zhang, Yu-Jie Qiao, Bin-Feng Yang, Ting Gong, Duo-Ming Zhao, Bang-Rong Huang

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A novel gene signature for predicting outcome in colorectal cancer patients based on tumor cell-endothelial cell interaction via single-cell sequencing and machine learning by Lina Pang, Qingxia Sun, Wenyue Wang, Mingjie Song, Ying Wu, Xin Shi, Xiaonan Shi

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A Comparison of Machine Learning-Based Approaches in Estimating Surface PM_2.5 Concentrations Focusing on Artificial Neural Networks and High Pollution Events by Shijin Wei, Kyle Shores, Yangyang Xu

Subjects: “…machine learning…”
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Enhancing Power Grid Reliability With Machine Learning and Auxiliary Classifier Generative Adversarial Networks: A Study on Fault Detection Using the Georgia Electric System Load Dataset by Hafeez Ur Rehman Siddiqui, Robert Brown, Adil Ali Saleem, Muhammad Amjad Raza, Sandra Dudley

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Machine learning models for dementia screening to classify brain amyloid positivity on positron emission tomography using blood markers and demographic characteristics: a retrospective observational study by Noriyuki Kimura, Kotaro Sasaki, Teruaki Masuda, Takuya Ataka, Mariko Matsumoto, Mika Kitamura, Yosuke Nakamura, Etsuro Matsubara

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Predicting the heat capacity of strontium-praseodymium oxysilicate SrPr4(SiO4)3O using machine learning, deep learning, and hybrid models by Amir Hossein Sheikhshoaei, Ali Khoshsima, Davood Zabihzadeh

Subjects: “…Machine learning…”
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Combining a Standardized Growth Class Assessment, UAV Sensor Data, GIS Processing, and Machine Learning Classification to Derive a Correlation with the Vigour and Canopy Volume of Grapevines by Ronald P. Dillner, Maria A. Wimmer, Matthias Porten, Thomas Udelhoven, Rebecca Retzlaff

“…To address these problems, based on a standardized growth class assessment, labeled ground truth data of precisely located grapevines were predicted with specifically selected Machine Learning (ML) classifiers (Random Forest Classifier (RFC), Support Vector Machines (SVM)), utilizing multispectral UAV (Unmanned Aerial Vehicle) sensor data. …”
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Smart GNSS Integrity Monitoring for Road Vehicles: An Overview of AI Methods by Ines Viveiros, Helder Silva, Yuri Andrade, Cristiano Pendao

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Delving into biomarkers and predictive modeling for CVD mortality: a 20-year cohort study by Zhen Wu, Abdullahi Mohamud Hilowle, Ying Zhou, Changlin Zhao, Shuo Yang

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Bending obstacles when moving a mobile robot by A. V. Sidorenko, N. A. Saladukha

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Calculer la sémantique avec le langage IEML by Pierre Lévy

Subjects: “…machine learning…”
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Explainable analysis of infrared and visible light image fusion based on deep learning by Bo Yuan, Hongyu Sun, YinJing Guo, Qiang Liu, Xinghao Zhan

Subjects: “…Machine learning…”
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Streamflow prediction using artificial neural networks and soil moisture proxies by Robert Edwin Rouse, Doran Khamis, Scott Hosking, Allan McRobie, Emily Shuckburgh

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Tailoring convolutional neural networks for custom botanical data by Jamie R. Sykes, Katherine J. Denby, Daniel W. Franks

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Conservative Interference Injection to Minimize Wi-Fi Sensing Privacy Risks and Bandwidth Loss by Aryan Sharma, Haoming Wang, Deepak Mishra, Aruna Seneviratne

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Deep Learning-Based Robust Automated System for Predicting Human Sperm DNA Fragmentation Index by Roopini Sathiasai Kumar, Swapnil Sharma, Arunima Halder, Vipin Gupta

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Pedestrian inertial navigation: An overview of model and data-driven approaches by Itzik Klein

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Machine and Deep Learning Models for Stress Detection Using Multimodal Physiological Data by Eman Abdelfattah, Shreehar Joshi, Shreekar Tiwari

Subjects: “…Machine learning…”
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