Optimization of Convolutional Neural Networks With Multi-Objective Function Metaheuristics for Melanoma Detection by Pamela Hermosilla, Ricardo Soto, Eric Monfroy, Emanuel Vega, Lucas Erazo, Valentina Guzman

“…This article explores 45 recent research contributions addressing melanoma classification, offering a critical overview of current trends and techniques. …”
Get full text

Wheat Powdery Mildew Severity Classification Based on an Improved ResNet34 Model by Meilin Li, Yufeng Guo, Wei Guo, Hongbo Qiao, Lei Shi, Yang Liu, Guang Zheng, Hui Zhang, Qiang Wang

“…Crop disease identification is a pivotal research area in smart agriculture, forming the foundation for disease mapping and targeted prevention strategies. …”
Get full text

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China by Weizi Wu, Li Jing, Qing Peng, Peng Hua, Zeng Shumei, Luofang Lv, Liqing Yue, Hu Jian zhong, Huang Weihong

Get full text

Predicting the Relative Density of Stainless Steel and Aluminum Alloys Manufactured by L-PBF Using Machine Learning by José Luis Mullo, Iván La Fé-Perdomo, Jorge Ramos-Grez, Ángel F. Moreira Romero, Alejandra Ramírez-Albán, Mélany Yarad-Jácome, Germán Omar Barrionuevo

“…This study presents a compendium of data for the additive fabrication of stainless steel and aluminum alloys, offering researchers a guide to understanding how processing parameters influence RD.…”
Get full text

Ensemble deep learning and anomaly detection framework for automatic audio classification: Insights into deer vocalizations by Salem Ibrahim Salem, Sakae Shirayama, Sho Shimazaki, Kazuo Oki

“…By incorporating advanced machine learning models into environmental monitoring, we have paved the way for more data-driven approaches in wildlife research.…”
Get full text

Using Permutation-Based Feature Importance for Improved Machine Learning Model Performance at Reduced Costs by Adam Khan, Asad Ali, Jahangir Khan, Fasee Ullah, Muhammad Faheem

“…These high computational costs and uncertain payoffs make most Software engineering researchers reluctant to optimize ML models. This creates a need for novel techniques that can achieve near-optimal performance of hyperparameter settings while maintaining the computational efficiency of default settings. …”
Get full text

Integrating vision transformer-based deep learning model with kernel extreme learning machine for non-invasive diagnosis of neonatal jaundice using biomedical images by M. Eliazer, Sibi Amaran, K. Sreekumar, A. Vikram, Gyanendra Prasad Joshi, Woong Cho

“…Therefore, appropriate technologies are instantly required. Nowadays, researchers have begun to implement an image-processing model for analyzing jaundice. …”
Get full text

Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data by Abu Bakker Siddique, Tanveer Alam Munshi, Nazmul Islam Rakin, Mahamudul Hashan, Sushmita Sarker Chnapa, Labiba Nusrat Jahan

“…Using a few petrophysical, drilling, and well log data, the methodology presented in this work can help engineers and researchers quickly and precisely determine the reservoir pore pressure, validating the safe and cost-effective drilling operations.…”
Get full text

Hybrid Deep Learning and Fuzzy Matching for Real-Time Bidirectional Arabic Sign Language Translation: Toward Inclusive Communication Technologies by Mogeeb A. A. Mosleh, Ahmed A. A. Mohammed, Ezzaldeen E. A. Esmail, Rehab A. A. Mohammed, Basheer Almuhaya

“…Therefore, a bidirectional real-time translation application for Arabic Sign Language and written Arabic text was developed in this research to improve communication and learning experiences for individuals who are deaf. …”
Get full text

Application of Mask R-CNN for automatic recognition of teeth and caries in cone-beam computerized tomography by Yujie Ma, Maged Ali Al-Aroomi, Yutian Zheng, Wenjie Ren, Peixuan Liu, Qing Wu, Ye Liang, Canhua Jiang

“…Abstract Objectives Deep convolutional neural networks (CNNs) are advancing rapidly in medical research, demonstrating promising results in diagnosis and prediction within radiology and pathology. …”
Get full text

Mapping Soil Available Nitrogen Using Crop-Specific Growth Information and Remote Sensing by Xinle Zhang, Yihan Ma, Shinai Ma, Chuan Qin, Yiang Wang, Huanjun Liu, Lu Chen, Xiaomeng Zhu

“…The research results indicate that (1) the introduction of growth information at different growth periods of soybean and maize has different effects on the accuracy of soil AN mapping. …”
Get full text

Metaparameter optimized hybrid deep learning model for next generation cybersecurity in software defined networking environment by C. Labesh Kumar, Suresh Betam, Denis Pustokhin, E. Laxmi Lydia, Kanchan Bala, Rajanikanth Aluvalu, Bhawani Sankar Panigrahi

“…Deep Learning (DL) is one of the influential models useful in cyber-security, and numerous Network Intrusion Detection (NIDS) were developed in current studies. Some researchers have specified that deep neural networks (DNN) subtly perceive adversarial assaults. …”
Get full text

Implementation of Machine Vision Methods for Cattle Detection and Activity Monitoring by Roman Bumbálek, Tomáš Zoubek, Jean de Dieu Marcel Ufitikirezi, Sandra Nicole Umurungi, Radim Stehlík, Zbyněk Havelka, Radim Kuneš, Petr Bartoš

“…The goal of this research was to implement machine vision algorithms in a cattle stable to detect cattle in stalls and determine their activities. …”
Get full text

On the interpretability of the SVM model for predicting infant mortality in Bangladesh by Md Abu Sayeed, Azizur Rahman, Atikur Rahman, Rumana Rois

“…Interpretable ML is, therefore, an emerging research field that combines the performance and interpretability of ML models to create comprehensive solutions for complex decision-making analysis. …”
Get full text

Intelligent irrigation strategy model for farmland using dung beetle optimization-random forest algorithms by Wenwen Hu, Yong Liu, Jun An, Shipu Xu, Zhiwen Zhou, Mingming An, Xiaokun Guo, Xiang Ma, Wenfei Jiang, Yunsheng Wang

“…Testing across diverse datasets revealed the DBO-RF model possesses robust generalization capability and consistently high predictive performance. This research provides valuable insights into agricultural meteorological data analysis and irrigation management, particularly for complex, multi-source data. …”
Get full text

Predictive model for sarcopenia in chronic kidney disease: a nomogram and machine learning approach using CHARLS data by Renjie Lu, Shiyun Wang, Pinghua Chen, Fangfang Li, Fangfang Li, Pan Li, Qian Chen, Xuefei Li, Fangyu Li, Suxia Guo, Jinlin Zhang, Jinlin Zhang, Dan Liu, Zhijun Hu

“…Four machine learning algorithms were utilized, with the optimal model undergoing hyperparameter optimization to evaluate the significance of predictive factors.ResultsA total of 1,092 CKD patients were included, with 231 (21.2%) diagnosed with sarcopenia. …”
Get full text

Semantic Reasoning Using Standard Attention-Based Models: An Application to Chronic Disease Literature by Yalbi Itzel Balderas-Martínez, José Armando Sánchez-Rojas, Arturo Téllez-Velázquez, Flavio Juárez Martínez, Raúl Cruz-Barbosa, Enrique Guzmán-Ramírez, Iván García-Pacheco, Ignacio Arroyo-Fernández

“…Their interpretability, minimal hardware footprint, and open weights promote equitable AI research, opening new avenues for automated NCD knowledge synthesis, surveillance, and decision support.…”
Get full text

Classification performance and reproducibility of GPT-4 omni for information extraction from veterinary electronic health records by Judit M. Wulcan, Kevin L. Jacques, Mary Ann Lee, Samantha L. Kovacs, Nicole Dausend, Lauren E. Prince, Jonatan Wulcan, Sina Marsilio, Stefan M. Keller

Get full text

Evapotranspiration Partitioning in Selected Subtropical Fruit Tree Orchards Based on Sentinel 2 Data Using a Light Gradient-Boosting Machine (LightGBM) Learning Model in Malelane,... by Prince Dangare, Zama E. Mashimbye, Paul J. R. Cronje, Joseph N. Masanganise, Shaeden Gokool, Zanele Ntshidi, Vivek Naiken, Tendai Sawunyama, Sebinasi Dzikiti

Get full text

Analysis, Forecasting, and System Identification of a Floating Offshore Wind Turbine Using Dynamic Mode Decomposition by Giorgio Palma, Andrea Bardazzi, Alessia Lucarelli, Chiara Pilloton, Andrea Serani, Claudio Lugni, Matteo Diez

Get full text