UOrtos: Methodology for Co-Registration and Subpixel Georeferencing of Satellite Imagery for Coastal Monitoring by Gonzalo Simarro, Daniel Calvete, Francesca Ribas, Yeray Castillo, Càrol Puig-Polo

“…This study introduces a novel methodology for the automated co-registration and georeferencing of satellite imagery to enhance the accuracy of shoreline detection and coastal monitoring. The approach utilizes feature-based methods, cross-correlation, and RANSAC (RANdom SAmple Consensus) algorithms to accurately align images while avoiding outliers. …”
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Analysis of multiple faults in induction motor using machine learning techniques by Puja Pohakar, Ravi Gandhi, Surender Hans, Gulshan Sharma, Pitshou N. Bokoro

“…Based on key operating parameters like voltage, current, and speed, this article describes how machine learning (ML) algorithms like Random Forest (RF), K-Nearest Neighbors (KNN), Gradient Boosting Machine (GBM), Support Vector Machines (SVM), and Extreme Gradient Boosting with Feature Interaction (XGBoost + FIS) are used to detect different motor faults. …”
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Comparative Analysis of Random Forest and Logistic Regression Methods in Predicting Leukemia Blood Cancer Using Microscopic Blood Cell Images by Jepri Banjarnahor, Galuh Wira Relungwangi

“…These findings suggest that ensemble methods like RF are particularly well-suited for detecting one of the most deadly blood cancers, leukemia, due to their ability to handle complex feature interactions in medical imaging data. …”
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Ensemble Learning-Based Alzheimer’s Disease Classification Using Electroencephalogram Signals and Clock Drawing Test Images by Young Jae Huh, Jun-ha Park, Young Jae Kim, Kwang Gi Kim

“…In this research, we demonstrate that three machine learning algorithms, trained on an ensemble of electroencephalogram (EEG) and clock drawing test (CDT) feature data for an AD classification task, show improved AD detection accuracy compared to when either the EEG or CDT dataset is used independently. …”
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Optimized Identity Authentication via Channel State Information for Two-Factor User Verification in Information Systems by Chuangeng Tian, Fanjia Li, Xiaomeng Liu, Juanjuan Li

“…Feature extraction is further optimized through a dual-threshold moving window detection algorithm for precise activity segmentation, a subcarrier selection method to filter redundant or unstable channels, and principal component analysis (PCA) to reduce feature dimensionality while retaining 90% of critical information. …”
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Kernel machine tests of association using extrinsic and intrinsic cluster evaluation metrics. by Alexandria M Jensen, Peter DeWitt, Brianne M Bettcher, Julia Wrobel, Katerina Kechris, Debashis Ghosh

“…The literature on analysis of these community detection algorithms has focused on comparing them within the same subject. …”
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Point Data Registration With the Multi-Object, Cardinalized Optimal Linear Assignment Metric by Pablo A. Barrios, Vicente Guzman, Martin D. Adams, Claudio A. Perez

“…This allows robust scan registration to take place in the presence of unknown point correspondences and inter-scan translation and orientation as well as point cloud detection and spatial errors. The resulting Particle Swarm Optimization (PSO)-COLA registration algorithm is capable of determining inter-scan point correspondences, but can also run based on point correspondences determined by other algorithms, such as the application of Fast Point Feature Histograms (FPFH) descriptors. …”
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Resting Posture Recognition Method for Suckling Piglets Based on Piglet Posture Recognition (PPR)–You Only Look Once by Jinxin Chen, Luo Liu, Peng Li, Wen Yao, Mingxia Shen, Longshen Liu

“…Secondly, to overcome the limitations of the YOLOv11 model in fine feature extraction and small object detection, improvements are made, resulting in the proposed PPR-YOLO model. …”
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Transfer Learning for Induction Motor Health Monitoring: A Brief Review by Prashant Kumar

“…These sophisticated deep learning algorithms have been widely used for induction motor health monitoring due to their autonomous feature extraction abilities and end-to-end learning capabilities. …”
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Research on improving the ranging accuracy of ships with stereo vision through Kalman filter optimization. by Zhongbo Peng, Jie Han, Liang Tong, Lumeng Wang, Dan Liu, Shijie Sun

“…This algorithm, based on YOLOv5s, utilizes the lightweight MobileNetV3-Small network to replace the original YOLOv5s feature extraction backbone network, thereby improving the detection speed. …”
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Variational Approach for Learning Community Structures by Jun Jin Choong, Xin Liu, Tsuyoshi Murata

“…In domains such as biology, chemistry, and physics, researchers often rely on community detection algorithms to uncover community structures from complex systems yet no unified definition of community structure exists. …”
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Comparison of Machine Learning Models for Classification of Breast Cancer Risk Based on Clinical Data by Haniyeh Rafiepoor, Alireza Ghorbankhanloo, Kazem Zendehdel, Zahra Zangeneh Madar, Sepideh Hajivalizadeh, Zeinab Hasani, Ali Sarmadi, Behzad Amanpour‐Gharaei, Mohammad Amin Barati, Mozafar Saadat, Seyed‐Ali Sadegh‐Zadeh, Saeid Amanpour

“…Ten classification algorithms were applied to the dataset. The accuracy, sensitivity, precision, and feature importance in the machine learning algorithms were assessed and compared to previous studies for evaluation. …”
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The Talent Cultivation Model of Study Travel Majors in Universities Based on the Internet of Things and Deep Learning by Yanjie Zhan

“…The system utilizes IoT devices to collect real-time data on students’ learning behaviors, social interactions, and environmental perceptions, which are then analyzed through multi-level feature extraction and deep learning algorithms. The research data comes from publicly available course data such as those from Coursera, encompassing multimodal information including video lectures, text materials, interaction records, and virtual environment perception data. …”
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Diagnostic Models for Differentiating COVID-19-Related Acute Ischemic Stroke Using Machine Learning Methods by Eylem Gul Ates, Gokcen Coban, Jale Karakaya

“…Various feature selection algorithms were applied to identify the most relevant features, which were then used to train and evaluate machine learning classification models. …”
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FocusDet: an efficient object detector for small object by Yanli Shi, Yi Jia, Xianhe Zhang

“…It consists of three parts: backbone, feature fusion structure, and detection head. STCF-EANet was used as the backbone for feature extraction, the Bottom Focus-PAN for feature fusion, and the detection head for object localization and recognition.To maintain sufficient global context information and extract multi-scale features, the STCF-EANet network backbone is used as the feature extraction network.PAN is a feature fusion module used in general object detectors. …”
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AGU2-Net: Multi-Scale U²-Net Enhanced by Attention Gate Mechanism for Image Tampering Localization by Kefei Wu, Lin Li, Qingyan Li

“…Although deep learning algorithms based on convolutional neural networks (CNNs) have made notable progress in image forgery detection, they still face certain limitations in effectively detecting and localizing tampered areas due to the subtle nature of existing manipulation traces. …”
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Predicting cancer risk using machine learning on lifestyle and genetic data by Mohamed Abdelmoaty Ahmed, Ahmed AbdelMoety, Asmaa Mohamed Ahmed Soliman

“…Abstract Cancer remains one of the leading causes of mortality worldwide, where early detection significantly improves patient outcomes and reduces treatment burden. …”
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Hybrid Series of Carbon‐Vacancy Electrodes for Multi Chemical Vapors Diagnosis Using a Residual Multi‐Task Model by Tianci Liu, Yun Ji Hwang, Lu Zhang, Jongwoo Hong, Teajong Hwang, Seong Chan Jun

“…However, substantial challenges and opportunities remain in the simultaneous detection and classification of multiple gases. Artificial intelligence (AI) integrated gas sensor systems effectively enable multi‐gas detection using specialized algorithms. …”
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Exploring deep learning for landslide mapping: A comprehensive review by Zhi-qiang Yang, Wen-wen Qi, Chong Xu, Xiao-yi Shao

“…Recent advancements in high-resolution satellite imagery, coupled with the rapid development of artificial intelligence, particularly data-driven deep learning algorithms (DL) such as convolutional neural networks (CNN), have provided rich feature indicators for landslide mapping, overcoming previous limitations. …”
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Privacy-Oriented Successive Approximation Image Position Follower Processing by Ying Miao, Danyang Shao, Zhimin Yan

“…The detection of human key points depends on the human pose estimation algorithm, so the research in this paper is based on the bottom-up model in the multiperson pose estimation method; firstly, all the human key points in the image are detected by feature extraction through the convolutional neural network, and then the accurate labelling of human key points is achieved by using the heat map and offset fusion optimization method in the feature point confidence map prediction, and finally, the human body detection results are obtained. …”
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