Dual-Phase Severity Grading of Strawberry Angular Leaf Spot Based on Improved YOLOv11 and OpenCV by Yi-Xiao Xu, Xin-Hao Yu, Qing Yi, Qi-Yuan Zhang, Wen-Hao Su

“…The enhanced You Only Look Once version 11 (YOLOv11) architecture incorporated a Content-Aware ReAssembly of FEatures (CARAFE) module for improved feature upsampling and a squeeze-and-excitation (SE) attention mechanism for channel-wise feature recalibration, resulting in the YOLOv11-CARAFE-SE for the severity assessment of strawberry angular leaf spot. …”
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CloudSense: A model for cloud type identification using machine learning from radar data by Mehzooz Nizar, Jha K. Ambuj, Manmeet Singh, S.B. Vaisakh, G. Pandithurai

“…CloudSense generated results are also compared against conventional radar algorithms and we find that CloudSense performs better than radar algorithms. …”
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Basketball teaching methods based on 3D-Convolutional neural network by Chao Huang, Xian Wu

“…The optimized algorithm is then used for video skilled movement detection processing to obtain cropped frame images. …”
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Comparison and Evaluation of Rain Gauge, CMORPH, TRMM PR and GPM DPR KuPR Precipitation Products over South China by Rui Wang, Huiping Li, Hao Huang, Liangliang Li

“…Several statistical metrics suggest that although the missing detection rates of TRMM and GPM are higher than those of CMORPH (probability of detection 10–60%), their false detection rates are spatially lower (false alert ratio 10–30%) in Middle-East China. …”
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Rapid and Accurate Measurement of Major Soybean Components Using Near-Infrared Spectroscopy by Chenxiao Li, Jiatong Yu, Sheng Wang, Qinglong Zhao, Qian Song, Yanlei Xu

“…To improve model robustness, preprocessing strategies such as standard normal variate (SNV), multiplicative scatter correction (MSC), and Savitzky–Golay derivatives were applied. Feature selection was conducted using competitive adaptive reweighted sampling (CARS), successive projections algorithm (SPA), and uninformative variable elimination (UVE), followed by model construction with partial least squares regression (PLSR), support vector regression (SVR), and random forest (RF). …”
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Machine learning modeling of cancer treatment-related cardiac events in breast cancer: utilizing dosiomics and radiomics by Sefika Dincer, Muge Akmansu, Oya Akyol

“…Machine learning models were optimized using the Tree-based Pipeline Optimization Tool (TPOT), identifying the gradient-boosted classification as the best-performing algorithm. Feature selection was conducted using gradient-boosted recursive feature elimination. …”
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Bioinformatics and machine learning-driven key genes screening for vortioxetine by Sabire Kılıçarslan, Meliha Merve Hız

“…After feature selection for the cleaned dataset, machine learning algorithms such as the K-nearest neighbors' algorithm, Naive Bayes, and Support Vector Machine (SVM) were used. …”
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Explainable Artificial Intelligence Models for Predicting Depression Based on Polysomnographic Phenotypes by Doljinsuren Enkhbayar, Jaehoon Ko, Somin Oh, Rumana Ferdushi, Jaesoo Kim, Jaehong Key, Erdenebayar Urtnasan

“…This study aimed to develop explainable artificial intelligence (AI) models to predict depression using polysomnographic phenotype data, ensuring high predictive performance while providing clear insights into the importance of features influencing the risk of depression. Advanced machine learning algorithms such as random forest, extreme gradient boosting, categorical boosting, and light gradient boosting machines were employed to train and validate the predictive AI models. …”
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A Hybrid Machine Learning Model for Accurate Autism Diagnosis by Durga Prasad Kavadi, Venkata Rami Reddy Chirra, Palacharla Ravi Kumar, Sai Babu Veesam, Sagar Yeruva, Lalitha Kumari Pappala

“…The proposed model employs an improved Squirrel Search Algorithm-based Feature Selection (ISSA-FS) to identify the most relevant features from medical data. …”
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Intelligent Perception and Seam Tracking System for Thick Plate Weldments Based on Constant-Focus Optical Path by Lei Zhai, Wenze Ren, Fei Li, Rong Wu, Jinsong Lin, Jiahui Feng, Jun Zheng, Yang Liu

“…Furthermore, a sophisticated feature point extraction algorithm, which integrates a maximum distance search strategy with a least-squares fitting procedure, was developed to facilitate the precise and timely identification of weld seam characteristic points. …”
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Intelligent Diagnosis of Rolling Element Bearings Under Various Operating Conditions Using an Enhanced Envelope Technique and Transfer Learning by Ali Davoodabadi, Mehdi Behzad, Hesam Addin Arghand, Somaye Mohammadi, Len Gelman

“…The results show that transfer learning with fine-tuning, combined with the resonance region identification algorithm, significantly enhances fault detection accuracy. …”
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Human fall direction recognition in the indoor and outdoor environment using multi self-attention RBnet deep architectures and tree seed optimization by Awais Khan, Jung-Yeon Kim, Chomyong Kim, Muhammad Attique Khan, Hyojin Shin, Jiyoung Woo, Yunyoung Nam

“…The 7-RBNet and 9-RBNet self-attention models demonstrated superior accuracy and precision rates, leading us to exclude the 3-RBNet self model from further analysis. To optimize feature selection and improve classification performance while reducing computational costs, we employed the tree seed algorithm on the self-attention features of 7-RBNet and 9-RBNet self-attention models. …”
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A Visual Measurement Method for Large-Sized Parts by Junkai Yang

“…The method utilizes the edge detection pixel point data of the part image for searching and region localization of line and circle features in the image with a modified Hough transform; A geometric calculation is used to compute the coordinates of the point cloud within the feature area; Drawing on the idea of graph neural network, the priori knowledge of machining is utilized to establish the correlation of related dimensional features in the part drawing, and this is used to propose a model of dimensional validation and correction by the combination of different features. …”
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Wavelet-Analysis of Cardiosignals Using Matlab by B. F. Badalyan, H. A. Gomtsyan, S. G. Gomtsyan

“…This article is devoted to the problem of accurate detection of cardiosignal QRS-complexes for early diagnosis of various diseases of human cardiovascular system. …”
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An integrated calcium imaging processing toolbox for the analysis of neuronal population dynamics. by Sebastián A Romano, Verónica Pérez-Schuster, Adrien Jouary, Jonathan Boulanger-Weill, Alessia Candeo, Thomas Pietri, Germán Sumbre

“…The toolbox includes newly developed algorithms and interactive tools for image pre-processing and segmentation, estimation of significant single-neuron single-trial signals, mapping event-related neuronal responses, detection of activity-correlated neuronal clusters, exploration of population dynamics, and analysis of clusters' features against surrogate control datasets. …”
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Analisis Algoritma Klasifikasi Untuk Mengidentifikasi Potensi Risiko Kesehatan Ibu Hamil by Jajang Jaya Purnama, Nina Kurnia Hikmawati, Sri Rahayu

“… The health of pregnant women has an important aspect in efforts to achieve the birth of a healthy baby. So early detection of the health of pregnant women has important. …”
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Enhancing Crop Health: Advanced Machine Learning Techniques for Prediction Disease in Palm Oil Tree by Nandy Manish, Kumar Yalakala Dinesh

“…Palm oil trees are one of the key crops in the world's agricultural economy yet they are vulnerable to a number of diseases which can reduce yields substantially. Currently disease detection and management is usually labor intensive and slow, thus delays in detection and response and increased losses in yields. …”
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Diet Engine: A real-time food nutrition assistant system for personalized dietary guidance by Asim Moin Saad, Md. Raihanul Haque Rahi, Md. Manirul Islam, Gulam Rabbani

“…By seamlessly integrating advanced deep learning algorithms with user-centric features, this study underscores the transformative potential of Diet Engine in fostering healthier eating habits, raising nutritional awareness, and contributing to a global shift toward more informed and sustainable lifestyle choices.…”
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Sparse Convolution FPGA Accelerator Based on Multi-Bank Hash Selection by Jia Xu, Han Pu, Dong Wang

“…Reconfigurable processor-based acceleration of deep convolutional neural network (DCNN) algorithms has emerged as a widely adopted technique, with particular attention on sparse neural network acceleration as an active research area. …”
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A SAR-based flood mapping approach: application of SAR-SIFT registration and modified DeepLabV3 segmentation in flood hazard assessment by Zhuoyu Zhang, Jiaqi Xiong, Xiang Li, Yu Li, Junrong Liu

“…An innovative framework for rapid flood detection leverages Synthetic Aperture Radar (SAR) to overcome cloud obstruction and geolocation inaccuracies. …”
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