Comparative Study of Cell Nuclei Segmentation Based on Computational and Handcrafted Features Using Machine Learning Algorithms by Rashadul Islam Sumon, Md Ariful Islam Mozumdar, Salma Akter, Shah Muhammad Imtiyaj Uddin, Mohammad Hassan Ali Al-Onaizan, Reem Ibrahim Alkanhel, Mohammed Saleh Ali Muthanna

“…We employed several methods, including K-means clustering, Random Forest (RF), Support Vector Machine (SVM) with handcrafted features, and Logistic Regression (LR) using features derived from Convolutional Neural Networks (CNNs). …”
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BED-YOLO: An Enhanced YOLOv10n-Based Tomato Leaf Disease Detection Algorithm by Qing Wang, Ning Yan, Yasen Qin, Xuedong Zhang, Xu Li

“…In this paper, we propose an improved tomato leaf disease detection method based on the YOLOv10n algorithm, named BED-YOLO. …”
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CGA-Net: A CNN-GAT Aggregation Network Based on Metric for Change Detection in Remote Sensing by Huilan Lin, Chunlei Zhao, Rong He, Ming Zhu, Xin Jiang, Yi Qin, Wen Gao

“…Attempting to solve the problems in existing object-level change detection methods, such as ignoring the relationship between dual-branch features, insufficient utilization of feature point information, and unreasonable fusion weight allocation mechanism, this article proposes an object-level change detection network, CGA-Net, based on metric, which combines similarity measurement with the feature extraction and fusion. …”
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Thermographic Data Processing and Feature Extraction Approaches for Machine Learning-Based Defect Detection by Alexey Moskovchenko, Michal Svantner

“…Infrared thermography is a non-destructive testing method used to detect defects in materials and structures. Machine learning algorithms have been applied to thermographic data to automate the defect detection process. …”
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AccFIT-IDS: accuracy-based feature inclusion technique for intrusion detection system by C. Rajathi, P. Rukmani

“…To address this, the study proposed AccFIT (Accuracy-based Feature Inclusion Technique) for IDS, combining two-stage Feature Selection Algorithms (FSA). …”
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Motion feature extraction using magnocellular-inspired spiking neural networks for drone detection by Jiayi Zheng, Jiayi Zheng, Yaping Wan, Xin Yang, Hua Zhong, Minghua Du, Gang Wang, Gang Wang

“…To address this, inspired by the magnocellular motion processing mechanisms, we proposed to utilize the spatial–temporal characteristics of the flying drones based on spiking neural networks, thereby developing the Magno-Spiking Neural Network (MG-SNN) for drone detection. The MG-SNN can learn to identify potential regions of moving targets through motion saliency estimation and subsequently integrates the information into the popular object detection algorithms to design the retinal-inspired spiking neural network module for drone motion extraction and object detection architecture, which integrates motion and spatial features before object detection to enhance detection accuracy. …”
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Explainable AI-Based Skin Cancer Detection Using CNN, Particle Swarm Optimization and Machine Learning by Syed Adil Hussain Shah, Syed Taimoor Hussain Shah, Roa’a Khaled, Andrea Buccoliero, Syed Baqir Hussain Shah, Angelo Di Terlizzi, Giacomo Di Benedetto, Marco Agostino Deriu

“…To address these limitations, this study proposes a comprehensive pipeline combining transfer learning, feature selection, and machine-learning algorithms to improve detection accuracy. …”
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Mf-net: multi-feature fusion network based on two-stream extraction and multi-scale enhancement for face forgery detection by Hanxian Duan, Qian Jiang, Xin Jin, Michal Wozniak, Yi Zhao, Liwen Wu, Shaowen Yao, Wei Zhou

“…Current face forgery detection algorithms achieve high detection accuracy within-dataset. …”
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Study on Few-Shot Object Detection Approach Based on Improved RPN and Feature Aggregation by Qiyu Pan, Keyi Fu, Gaocai Wang

“…Compared to some mainstream few-shot object detection algorithms, the IFA-FSOD algorithm can select more accurate candidate boxes, addressing issues of missed high IoU candidate boxes and incomplete feature information capture, resulting in higher precision.…”
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Detecting tropical freshly-opened swidden fields using a combined algorithm of continuous change detection and support vector machine by Ningsang Jiang, Peng Li, Zhiming Feng

“…The first part of the Continuous Change Detection and Classification (CCDC) algorithm holds promising potential in capturing abrupt changes. …”
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The Value of Clinical Decision Support in Healthcare: A Focus on Screening and Early Detection by Hendrik Schäfer, Nesrine Lajmi, Paolo Valente, Alessandro Pedrioli, Daniel Cigoianu, Bernhard Hoehne, Michaela Schenk, Chaohui Guo, Ruby Singhrao, Deniz Gmuer, Rezwan Ahmed, Maximilian Silchmüller, Okan Ekinci

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Detection of terrain feature points from digital elevation models using contour context by Jiapei Hu, Xuejun Liu, Bo Wu

“…The study provides a robust mathematical model of terrain feature points and an effective algorithm for their extraction. …”
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FOA-BDNet: A behavior detection algorithm for elevator maintenance personnel based on first-order deep network architecture by Zengming Feng, Tingwen Cao

“…This paper proposes an elevator maintenance personnel behavior detection algorithm based on the first-order deep network architecture (FOA-BDNet). …”
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Fault detection for Li-ion batteries of electric vehicles with feature-augmented attentional autoencoder by Yunsheng Fan, Zhiwu Huang, Heng Li, Wei Yuan, Lisen Yan, Yongjie Liu, Zheng Chen

“…Then, the augmented features are input into the local outlier factor algorithm for battery fault detection. …”
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Dental bur detection system based on asymmetric double convolution and adaptive feature fusion by HongLing Hou, Ao Yang, Xiangyao Li, Kangkai Zhu, Yandi Zhao, Zhiqiang Wu

“…Our approach outperforms current detection algorithms in terms of detection capability and efficiency, presenting a new method for the precise detection and counting of elongated objects such as dental burs.…”
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HAF-YOLO: Dynamic Feature Aggregation Network for Object Detection in Remote-Sensing Images by Pengfei Zhang, Jian Liu, Jianqiang Zhang, Yiping Liu, Jiahao Shi

“…The growing use of remote-sensing technologies has placed greater demands on object-detection algorithms, which still face challenges. …”
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A novel feature extractor based on constrained cross network for detecting sleep state by Chenlei Tian, Fei Song

“…Most existing methods that utilize wrist-worn devices data for detection rely on heuristic algorithms or traditional machine learning, which suffer from low classification efficiency and insufficient accuracy. …”
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A Hierarchical Feature Fusion and Dynamic Collaboration Framework for Robust Small Target Detection by Xu Yan, Junliang Du, Xuan Li, Xiaoye Wang, Xiaoxuan Sun, Pochun Li, Hongye Zheng

“…To address this, this paper proposes a novel small target detection algorithm that integrates hierarchical feature fusion with a spatial dynamic collaboration mechanism. …”
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A Self-Supervised Feature Point Detection Method for ISAR Images of Space Targets by Shengteng Jiang, Xiaoyuan Ren, Canyu Wang, Libing Jiang, Zhuang Wang

“…The experiments demonstrate that SFPD has better performance in feature point detection and feature point matching than usual algorithms.…”
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Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion by Tursun Mamat, Abdukeram Dolkun, Runchang He, Yonghui Zhang, Zulipapar Nigat, Hanchen Du

“…Pavement distress is one of the most serious and prevalent diseases in pavement road detection. However, traditional methods for crack detection often suffer from low efficiency and limited accuracy, necessitating improvements in the accuracy of existing crack detection algorithms. …”
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