Comparative analysis of adaptive and general labeling methods for soybean leaf detection by Yuseok Jeong, Yuseok Jeong, Song Lim Kim, Thanh Tuan Thai, Thanh Tuan Thai, Thanh Tuan Thai, Anh Tuan Le, Anh Tuan Le, Chaewon Lee, Hyo Jun Bae, Inchan Choi, Sheikh Mansoor, Yong Suk Chung, Kyung-Hwan Kim

“…This study examines the influence of different labeling methods on the efficiency of artificial intelligence (AI) based soybean leaf detection. …”
Get full text

Intelligent regulation for cryptocurrency anti-money laundering: models, methods, and applications by ZHANG Yifei, YUAN Yong, YANG Dong, WANG Fei-Yue

“…First, the recent research progress on intelligent AML regulation for cryptocurrencies was systematically reviewed. The main models, methods, and application patterns in AML regulatory research were summarized from multiple dimensions, including traditional machine learning, deep learning, ensemble learning, graph analysis, and heuristic approaches. …”
Get full text

A Bias Injection Technique to Assess the Resilience of Causal Discovery Methods by Martina Cinquini, Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi, Riccardo Guidotti

Get full text

BIOFEEDBACK AS A METHOD FOR STUDENTS’ MENTAL STATE ASSESSMENT by M. Yu. Ababkova, V. L. Leontieva

Subjects: Get full text

Building pre-service teachers’ resilience through Service-Learning: an explanatory sequential mixed methods study by Marta Sánchez-Jiménez, Marta Sánchez-Jiménez, María Maravé-Vivas, Jesús Gil-Gómez, Celina Salvador-Garcia

Subjects: Get full text

Dynamics-based predictions of infinite-dimensional complex systems using dynamical system deep learning method by Hao Li, Jianping Li, Zixiang Wu, Mingyu Wang, Guangcan Liu, Ruipeng Sun, Ruize Li, Ning Wang, Houbin Song, Shixin Zhen

Subjects: Get full text

Synchronous Analysis of Speech Production and Lips Movement to Detect Parkinson’s Disease Using Deep Learning Methods by Cristian David Ríos-Urrego, Daniel Escobar-Grisales, Juan Rafael Orozco-Arroyave

Get full text

Predicting Travel Insurance Purchases in an Insurance Firm through Machine Learning Methods after COVID-19 by Shiuh Tong Lim, Joe Yee Yuan, Khai Wah Khaw, XinYing Chew

Get full text

Detection of Adversarial Attacks Using Deep Learning and Features Extracted From Interpretability Methods in Industrial Scenarios by Angel Luis Perales Gomez, Lorenzo Fernandez Maimo, Alberto Huertas Celdran, Felix J. Garcia Clemente

“…The framework relies on features extracted after applying interpretability methods to time-series data. These features will be used to train a new Deep Learning model that discriminates between adversarial and non-adversarial samples. …”
Get full text

Computational machine learning estimation of digitoxin solubility in supercritical solvent at different temperatures utilizing ensemble methods by Hadil Faris Alotaibi, Waqed H. Hassan, Ahmed Kateb Jumaah Al-Nussairi, Narinderjit Singh Sawaran Singh, Ahmed Salah Al-Shati, M. M. Rekha, Subhashree Ray, Aashna Sinha, Gunjan Garg

“…Employing AdaBoost as an ensemble method, predictions from Bayesian Ridge Regression (BRR), Gaussian process regression (GPR), and K-nearest neighbors (KNN) are amalgamated. …”
Get full text

Estimation of Silage Maize Plant Moisture Content Based on UAV Multispectral Data and Ensemble Learning Methods by Xuchun Li, Jixuan Yan, Caixia Huang, Weiwei Ma, Zichen Guo, Jie Li, Xiangdong Yao, Qihong Da, Kejing Cheng, Hongyan Yang

“…Plant moisture content (PMC) serves as a crucial indicator of crop water status, directly affecting agricultural productivity, product quality, and the effectiveness of precision irrigation. Conventional methods for PMC assessment predominantly rely on destructive sampling techniques, which are labor-intensive and impede real-time monitoring. …”
Get full text

Machine Learning Ensemble Methods for Co-Seismic Landslide Susceptibility: Insights from the 2015 Nepal Earthquake by Tulasi Ram Bhattarai, Netra Prakash Bhandary

Get full text

Doctoral training at the University of Medical Sciences of Cienfuegos using distance learning methods, in the days of COVID-19 by Miriam Iglesias León, Norma Mur Villar, Manuel Cortés Cortés, José Aurelio Diaz Quiñones, Maria Aurelia San Juan Bosch

“…<br /><strong>Results:</strong> it was evidenced that distant learning methods used originate a wide range of possibilities in the teaching / learning processes as technological artifacts of scientific production with high communicative and interactive potential.…”
Get full text

Machine Learning Methods as a Tool for Analysis and Prediction of Impact Resistance of Rubber–Textile Conveyor Belts by Miriam Andrejiova, Anna Grincova, Daniela Marasova, Zuzana Kimakova

“…The article focuses on the use of machine learning methods as one of the approaches to the analysis and prediction of the impact resistance of rubber–textile conveyor belts. …”
Get full text

Predicting Three-Dimensional (3D) Printing Product Quality with Machine Learning-Based Regression Methods by Ahmet Burak Tatar

“…This study examines how printing parameters affect the roughness, tensile strength, and elongation of 3D-printed parts used in various applications. Machine learning-based regression models were employed to optimize product quality. …”
Get full text

Machine Learning for Fire Safety in the Built Environment: A Bibliometric Insight into Research Trends and Key Methods by Mehmet Akif Yıldız

“…This study evaluates machine learning applications in fire safety using a comprehensive approach that combines bibliometric and content analysis methods. …”
Get full text

A Systematic Literature Review of Eye-Tracking and Machine Learning Methods for Improving Productivity and Reading Abilities by Lewis Arnold, Soniya Aryal, Brandon Hong, Mahiethan Nitharsan, Anaya Shah, Waasiq Ahmed, Zakariya Lilani, Wanzi Su, Davide Piaggio

“…This systematic literature review, following PRISMA guidelines, evaluates 1782 articles, with 42 studies ultimately included, assessing their quality using the Mixed Methods Appraisal Tool (MMAT). The selected studies are categorised into eye metric classification, measuring comprehension, measuring attention, and typography and typesetting. …”
Get full text

Using Unsupervised and Supervised Machine Learning Methods to Correct Offset Anomalies in the GOES‐16 Magnetometer Data by F. Inceoglu, Paul T. M. Loto'aniu

“…Abstract This study uses supervised and unsupervised machine learning (ML) methods to correct unwanted offsets observed in the NOAA GOES‐16 magnetometer data. …”
Get full text

Quality Assessment of MRI-Radiomics-Based Machine Learning Methods in Classification of Brain Tumors: Systematic Review by Shailesh S. Nayak, Saikiran Pendem, Girish R. Menon, Niranjana Sampathila, Prakashini Koteshwar

“…Open science practices: Machine learning using MRI radiomic features provides a simple, noninvasive, and cost-effective method for glioma classification, enhancing transparency, reproducibility, and collaboration within the scientific community.…”
Get full text

Identification of biomarkers related to Escherichia coli infection for the diagnosis of gastrointestinal tumors applying machine learning methods by Tingting Ge, Wei Wang, Dandan Zhang, Xubo Le, Lumei Shi

“…Hub genes were selected by machine learning methods to establish a diagnostic model. The diagnostic performance of the model was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC) and validated in three external datasets. …”
Get full text