Classification of forest development stages from national low-density lidar datasets: a comparison of machine learning methods by R. Valbuena, M. Maltamo, P. Packalen

“…However, to date, classification methods based on machine learning, which are fairly common in other remote sensing fields, such as land use / land cover classification using multispectral sensors, have been largely overseen in forestry applications of ALS. …”
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Lessons Learned From the Integration of Ambient Assisted Living Technologies in Older Adults’ Care: Longitudinal Mixed Methods Study by Oteng Ntsweng, Martin Kodyš, Zhi Quan Ong, Fang Zhou, Antoine de Marassé-Enouf, Ibrahim Sadek, Hamdi Aloulou, Sharon Swee-Lin Tan, Mounir Mokhtari

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Quinary Classification of Human Gait Phases Using Machine Learning: Investigating the Potential of Different Training Methods and Scaling Techniques by Amal Mekni, Jyotindra Narayan, Hassène Gritli

“…The second approach involves participant-based splitting, training on data from 80% of the individuals and testing on the remaining 20%. Preprocessing methods such as Min–Max Scaling (MMS), Standard Scaling (SS), and Principal Component Analysis (PCA) were applied to the dataset to ensure optimal performance of the machine learning models. …”
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Regression machine learning methods for isolation prediction and massive gain broadband MIMO antenna design for 28 GHz applications by Md.Ashraful Haque, Redwan A. Ananta, Jun-Jiat Tiang, Mouaaz Nahas, Md Afzalur Rahman, Narinderjit Singh Sawaran Singh

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Evaluating the change and trend of construction land in Changsha City based GeoSOS-FLUS model and machine learning methods by Zuopeng Zhang, Zhe Li, Zhirong Li

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Estimation of Moderate-Resolution Snow Depth in Xinjiang With Enhanced-Resolution Passive Microwave and Reanalysis Data by Machine Learning Methods by Yongchang Yan, Yan Qin, Yongqiang Liu, Yubao Qiu, Yang Liu

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Feasibility of face-to-face and online learning methods to provide nutrition education to midwives, general practice nurses and student nurses by Catherine Jane Lucas, Ellen Lyell, Britney Koch, Victoria Elder, Leanne Cummins, Sarah Lambert, Anne T McMahon, Karen E Charlton

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Exploring the influence of age on the causes of death in advanced nasopharyngeal carcinoma patients undergoing chemoradiotherapy using machine learning methods by Mengni Zhang, Shipeng Zhang, Xudong Ao, Lisha Liu, Shunlin Peng

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Rapeseed mapping using machine learning methods and Sentinel-1 time series coupled with growing degree-days information by Sami Najem, Nicolas Baghdadi, Ya Gao, Hassan Bazzi, Saeideh Maleki, Cassio Fraga Dantas, Dino Ienco

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Large Scale Mowing Event Detection on Dense Time Series Data Using Deep Learning Methods and Knowledge Distillation by T. Moumouris, V. Tsironis, A. Psalta, K. Karantzalos

“…This study presents a novel approach for large-scale mowing event frequency detection using dense time series data and deep learning (DL) methods. Leveraging Sentinel-2 and Landsat data, we developed a benchmark dataset of over 1,600 annotated parcels in Greece, capturing mowing events through photo-interpretation and Enhanced Vegetation Index (EVI) analysis. …”
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A global classification dataset of daytime and nighttime marine low-cloud mesoscale morphology based on deep-learning methods by Y. Wu, J. Liu, J. Liu, Y. Zhu, Y. Zhu, Y. Zhu, Y. Zhang, Y. Cao, Y. Cao, K.-E. Huang, B. Zheng, Y. Wang, Y. Li, Q. Wang, C. Zhou, Y. Liang, J. Sun, M. Wang, M. Wang, D. Rosenfeld, D. Rosenfeld

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Investigating the anti-obesity potential of Nelumbo nucifera leaf bioactive compounds through machine learning and computational biology methods by Hongyun Huang, Chengyu Liu, Can Cao, Moxi Chen, Ruyin Li, Jianchun Yu

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Exploring the impact of gamified learning on positive psychology in CALL environments: A mixed-methods study with Thai university students by Budi Waluyo, Francis G. Balazon

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Increasing load factor in logistics and evaluating shipment performance with machine learning methods: A case from the automotive industry by Raziye Kılıç Sarıgül, Burak Erkayman, Bilal Usanmaz

“…The average cost was used to evaluate the clusters obtained through the unsupervised methods, while classification performance was measured using supervised machine learning techniques. …”
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PCN: a deep learning approach to jet tagging utilizing novel graph construction methods and Chebyshev graph convolutions by Yash Semlani, Mihir Relan, Krithik Ramesh

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Genomic Selection in Alfalfa Across Multiple Ploidy Levels: A Comparative Study Using Machine Learning and Bayesian Methods by Xiaoyue Zhu, Ruixin Zhang, Tianxiang Zhang, Changhong Guo, Yongjun Shu

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A comparative assessment of causal machine learning and traditional methods for enhancing supply chain resiliency and efficiency in the automotive industry by Ishansh Gupta, Adriana Martinez, Sergio Correa, Hendro Wicaksono

“…Many companies still rely on traditional escalation methods, which may lack the precision and adaptability offered by modern technologies. …”
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The relationship between clinical subtypes, prognosis, and treatment in ICU patients with acute cholangitis using unsupervised machine learning methods by Yuanhui Sheng, Shan Xu, Shu Zhang, Dan Zhang

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Potential of machine learning methods in operational risk stratification in patients with coronary artery disease scheduled for coronary bypass surgery by E. Z. Golukhova, M. A. Keren, T. V. Zavalikhina, N. I. Bulaeva, D. S. Akatov, I. Yu. Sigaev, K. B. Yakhyaeva, D. A. Kolesnikov

Subjects: “…machine learning methods…”
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Exploring the Impact of Reciprocal Teaching Methods on Problem-Solving Skills, Learning Speed, Metacognitive Knowledge, and Academic Self-Concept by Soghra Ebrahimi Ghavam, Mahshid Pourhosein, Mehdi Aslanzadeh

“…Objective: The present study investigated the effectiveness of the reciprocal teaching method on problem-solving skills, learning speed, metacognitive knowledge, and academic self-concept of seventh-grade female students in Tehran city. …”
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