An intelligent prediction method for rock core integrity based on deep learning by Zhaoxia Hu, Hua Mei, Lei Yu

“…Then the fused feature layer is decoded by the feature decoder to output the detection results of rock core fissure. …”
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Optimized wavelength selection for eggplant seed vitality classification using information acquisition techniques by Bing Yang, Xuyang Liu, Dongfang Zhang, Dongfang Zhang, Xiaofei Fan, Xiaofei Fan, Bo Peng, Jun Zhang, Jun Zhang

“…An Enhanced Information Acquisition Optimization (EIAO) algorithm was proposed for feature selection, which successfully identified a minimal set of 23 key wavelengths. …”
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Machine Learning-Based Prediction of Postoperative Deep Vein Thrombosis Following Tibial Fracture Surgery by Humam Baki, İsmail Bülent Özçelik

“…A total of 42 predictive models were developed using combinations of six ML algorithms—logistic regression, support vector machine, random forest, extreme gradient boosting, Light Gradient Boosting Machine (LightGBM), and neural networks—and seven feature selection methods, including SHapley Additive exPlanations (SHAP), Least Absolute Shrinkage and Selection Operator (LASSO), Boruta, recursive feature elimination, univariate filtering, and full-variable inclusion. …”
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The Study of Roadside Visual Perception in Internet of Vehicles Based on Improved YOLOv5 and CombineSORT by LI Xiaohui, YANG Jie, XIA Qin

“…Compared to other commonly algorithms, this algorithm can simultaneously achieve higher detection accuracy and lower time cost for high volume intersections, offering good application prospects in vehicle road collaboration scenarios. …”
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DLML-PC: an automated deep learning and metric learning approach for precise soybean pod classification and counting in intact plants by Yixin Guo, Jinchao Pan, Xueying Wang, Hong Deng, Hong Deng, Mingliang Yang, Mingliang Yang, Enliang Liu, Qingshan Chen, Qingshan Chen, Rongsheng Zhu, Rongsheng Zhu

“…After 200 epochs, the recognition results of various object detection algorithms were compared to obtain the optimal model. …”
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Detección y diagnóstico de fallas en motores mediante el análisis de vibraciones aplicando técnicas de inteligencia artificial. by Jair Elías Araujo Vargas, Dilan Yesid Franklin Coronel, Victor Manuel Arias Ruiz

“…Therefore, the performance of different artificial intelligence algorithms in the field of fault detection and diagnosis using vibration analysis in motors was evaluated. …”
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An innovative approach to urban parks and perception: a cross-cultural analysis using big and small data by Siqi Lai, Brian Deal

“…This study integrates big data (online reviews, images) and small data (survey results) with large language models (LLMs) and object detection algorithms to analyze public perceptions of urban parks in Stockholm, New York, and Shanghai. …”
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mzGroupAnalyzer--predicting pathways and novel chemical structures from untargeted high-throughput metabolomics data. by Hannes Doerfler, Xiaoliang Sun, Lei Wang, Doris Engelmeier, David Lyon, Wolfram Weckwerth

“…At the same time it is impossible to handle the amount of data involved in a metabolomics analysis manually. Algorithms are therefore imperative to allow for automated m/z feature extraction and subsequent structure or pathway assignment. …”
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A Systematic Study on the Extraction and Image Reproduction of Ceramic Sculpture Artworks by Yuhong Wang

“…The results show that the feature points detected by the one-dimensional normal distribution algorithm are on average 0.1%, 0.5%, 1.7%, 4.4%, and 9.2%. …”
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Novel Condition Monitoring Method for Wind Turbines Based on the Adaptive Multivariate Control Charts and SCADA Data by Qinkai Han, Zhentang Wang, Tao Hu

“…After comparing the regression accuracy of several popular algorithms in the MRA, the random forest is adopted for feature selection and regression prediction. …”
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Computational intelligence investigations on evaluation of salicylic acid solubility in various solvents at different temperatures by Adel Alhowyan, Wael A. Mahdi, Ahmad J. Obaidullah

“…The dataset was preprocessed using the Standard Scaler to standardize it, ensuring each feature has a mean of zero and a standard deviation of one, followed by outlier detection with Cook’s distance. …”
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Sentiment Analysis for the 2024 DKI Jakarta Gubernatorial Election Using a Support Vector Machine Approach by Mariani Mariani, Dwi Shinta Angreni, Sri Khaerawati Nur, Rinianty Rinianty, Deni Luvi Jayanto

“…These findings illustrate the complexities of public discourse surrounding key political events, highlighting the model's efficacy and the nuances of sentiment detection. Moreover, discussions on model limitations elucidate areas for enhancement, suggesting future avenues including the adoption of more sophisticated algorithms and improved data processing techniques. …”
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Dual-stage gated segmented multimodal emotion recognition method by MA Fei, LI Shuzhi, YANG Feixia, XU Guangxian

“…Multimodal emotion recognition has broad applications in mental health detection and affective computing. However, most existing methods rely on either global or local features, neglecting the joint modeling of both, which limits emotion recognition performance. …”
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Early Attrition Prediction for Web-Based Interpretation Bias Modification to Reduce Anxious Thinking: A Machine Learning Study by Sonia Baee, Jeremy W Eberle, Anna N Baglione, Tyler Spears, Elijah Lewis, Hongning Wang, Daniel H Funk, Bethany Teachman, Laura E Barnes

“…Features involving passive detection of user behavior contributed the most to the prediction relative to other features. …”
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A predictive analytics approach with Bayesian-optimized gentle boosting ensemble models for diabetes diagnosis by Behnaz Motamedi, Balázs Villányi

“…Machine learning (ML) based models have garnered attention in the realm of predictive healthcare, with ensemble methods, in particular, bolstering algorithms to improve classification performance. Nevertheless, enhancing boosting algorithms to achieve superior predictive accuracy continues to be a difficult task. …”
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Evaluating Binary Classifiers for Cardiovascular Disease Prediction: Enhancing Early Diagnostic Capabilities by Paul Iacobescu, Virginia Marina, Catalin Anghel, Aurelian-Dumitrache Anghele

“…Cardiovascular disease (CVD) is a significant global health concern and the leading cause of death in many countries. Early detection and diagnosis of CVD can significantly reduce the risk of complications and mortality. …”
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A robot process automation based mobile application for early prediction of chronic kidney disease using machine learning by Md. Hasan Imam Bijoy, Md. Jueal Mia, Md. Mahbubur Rahman, Mohammad Shamsul Arefin, Pranab Kumar Dhar, Tetsuya Shimamura

“…The use of computer-aided automated diagnostics can assist nephrologists in early detection and accurate classification, which are essential for improving patient outcomes. …”
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An Automated Semantic Segmentation Methodology for Infrared Thermography Analysis of the Human Hand by Melchior Arnal, Cyprien Bourrilhon, Vincent Beauchamps, Fabien Sauvet, Hassan Zahouani, Coralie Thieulin

“…Thus, this technology can be used to study the long-term thermal kinetics of the human hand by automatic feature detection, even in situations where the hand temperature experiences a significant variation.…”
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Small Sample Fiber Full State Diagnosis Based on Fuzzy Clustering and Improved ResNet Network by Xiangqun Li, Jiawen Liang, Jinyu Zhu, Shengping Shi, Fangyu Ding, Jianpeng Sun, Bo Liu

“…The optical time domain reflectometer (OTDR) curve features of communication fibers exhibit subtle differences among their normal, subhealthy, and faulty operating states, making it challenging for existing machine learning-based fault diagnosis algorithms to extract these minute features. …”
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ES-Net Empowers Forest Disturbance Monitoring: Edge–Semantic Collaborative Network for Canopy Gap Mapping by Yutong Wang, Zhang Zhang, Jisheng Xia, Fei Zhao, Pinliang Dong

“…However, traditional monitoring methods have notable limitations: ground-based measurements are inefficient; remote-sensing interpretation is susceptible to terrain and spectral interference; and traditional algorithms exhibit an insufficient feature representation capability. …”
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