Research on Defect Detection of Bare Film in Landfills Based on a Temperature Spectrum Model by Feixiang Jia, Yayu Chen, Wei Hao

“…Due to the construction damage of high-density polyethylene film (HDPE) during the early stages of landfill construction and missed or faulty welding, this paper proposes a method based on the synchronous characteristic temperature differences between defective and intact areas of HDPE film. An image feature-edge-picking algorithm was used to detect various defects. …”
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An Accurate Book Spine Detection Network Based on Improved Oriented R-CNN by Haibo Ma, Chaobo Wang, Ang Li, Aide Xu, Dong Han

“…However, the varying tilt angles and diverse aspect ratios of books on library shelves often reduce the effectiveness of conventional object detection algorithms. To address these challenges, this study proposes an enhanced oriented R-CNN algorithm for book spine detection. …”
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Explainable Anomaly Detection Based on Operational Sequences in Industrial Control Systems by Ka-Kyung Kim, Joon-Seok Kim, Ieck-Chae Euom

“…Many anomaly detection algorithms based on deep learning models have good performance but often involve complex neural network structures, creating a black-box issue where users cannot interpret the decisions made by the models. …”
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RST-YOLOv8: An Improved Chip Surface Defect Detection Model Based on YOLOv8 by Wenjie Tang, Yangjun Deng, Xu Luo

“…We propose an enhanced chip surface defect detection algorithm based on an improved version of YOLOv8, termed RST-YOLOv8. …”
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Leveraging OGTT derived metabolic features to detect Binge-eating disorder in individuals with high weight: a “seek out” machine learning approach by Marianna Rania, Anna Procopio, Paolo Zaffino, Elvira Anna Carbone, Teresa Vanessa Fiorentino, Francesco Andreozzi, Cristina Segura-Garcia, Carlo Cosentino, Franco Arturi

“…Data from the classic (2 h) and the extended (5 h) glucose load were computed by multiple algorithms and two models with the most relevant features were trained to detect BED within the sample. …”
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Algorithm of the Investigator's and Body of Inquiry's Actions in Investigation of Cellular Frauds by Leila Y. Aksenova

“…Taking into account specific features of objective nature of the studied acts the author proves that it is necessary to make an algorithm of the investigator's and interrogation unit activities in investigation of cellular frauds. …”
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Multi-Scale Feature Fusion and Context-Enhanced Spatial Sparse Convolution Single-Shot Detector for Unmanned Aerial Vehicle Image Object Detection by Guimei Qi, Zhihong Yu, Jian Song

“…Experiments on two datasets (i.e., VisDrone and ARH2000; the latter dataset was created by the researchers) demonstrate that the MFFCESSC-SSD remarkably outperforms the performance of the SSD and numerous conventional object detection algorithms in terms of accuracy and efficiency.…”
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YOLO-SRSA: An Improved YOLOv7 Network for the Abnormal Detection of Power Equipment by Wan Zou, Yiping Jiang, Wenlong Liao, Songhai Fan, Yueping Yang, Jin Hou, Hao Tang

“…This paper proposes a YOLO-SRSA-based anomaly detection algorithm. For data enhancement, geometric and color transformations and rain-fog simulations are applied to preprocess the dataset, improving the model’s robustness in outdoor complex weather. …”
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Machine learning based multi-stage intrusion detection system and feature selection ensemble security in cloud assisted vehicular ad hoc networks by C. Christy, A. Nirmala, A. Mary Odilya Teena, A. Isabella Amali

“…A new method for improving VANET security, a multi-stage Lightweight IntrusionDetection System Using Random Forest Algorithms (MLIDS-RFA), focuses on feature selection and ensemble models based on machine learning (ML). …”
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MFFCI–YOLOv8: A Lightweight Remote Sensing Object Detection Network Based on Multiscale Features Fusion and Context Information by Sheng Xu, Lin Song, Junru Yin, Qiqiang Chen, Tianming Zhan, Wei Huang

“…This network combines multiscale feature fusion and contextual information to accurately detect objects in RSIs. …”
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Studying the performance of YOLOv11 incorporating DHSA BRA and PPA modules in railway track fasteners defect detection by Chengwei Zhang, Jiawei Zhu, Yihao Ma, Qingmei Huang

“…Abstract With the development of railway transportation and the advancement of deep learning, object detection algorithms are increasingly replacing manual inspection of track fasteners. …”
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A New Robust Algorithm for Fault-Plane Parameters Identification: The 2009 L’Aquila (Central Italy) Seismic Sequence Case by Annarita Mangiacapra, Zaccaria Petrillo, Sergio Scippacercola, Luisa Valoroso, Rosa Nappi, Giuliana Alessio, Simona Tripaldi

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An Investigation of Infrared Small Target Detection by Using the SPT–YOLO Technique by Yongjun Qi, Shaohua Yang, Zhengzheng Jia, Yuanmeng Song, Jie Zhu, Xin Liu, Hongxing Zheng

“…To detect and recognize small-size and submerged complex background targets in infrared images, we combine a dynamic receptive field fusion strategy and a multi-scale feature fusion mechanism to improve the detection performance of small targets significantly. …”
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Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization by Muhammad Umar, Muhammad Farooq Siddique, Niamat Ullah, Jong-Myon Kim

“…The genetic algorithm (GA) is used to optimize feature selection and ensure the selection of the most relevant features to further improve the model’s performance. …”
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A Fast and Cost-Effective Electronic Nose Model for Methanol Detection Using Ensemble Learning by Bilge Han Tozlu

“…A Voting Classifier, an ensemble model, was used with Linear Discriminant Analysis, Support Vector Machines, and Extra Trees algorithms. The Voting Classifier achieved 85.88% classification accuracy before and 81.85% after feature selection. …”
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Rapid detection of wheel tread defects for YOLO-v5 trains based on residual attention by ZHANG Changfan, XU Yifu, HE Jing, YANG Haonan

“…In respect of large noise interference of wheel tread and insufficient feature fusion of traditional detection algorithms, in order to achieve fast and accurate detection of wheel tread defects, a method for rapid detection of wheel tread defects for YOLO-v5 trains based on residual attention was proposed. …”
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Machine Learning Approaches for Fault Detection in Internal Combustion Engines: A Review and Experimental Investigation by A. Srinivaas, N. R. Sakthivel, Binoy B. Nair

“…This paper concludes with a review of the progress in fault identification in ICE components and prospects, highlighted by an experimental investigation using 16 machine learning algorithms with seven feature selection techniques under three load conditions to detect faults in a four-cylinder ICE. …”
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Dark Ship Detection via Optical and SAR Collaboration: An Improved Multi-Feature Association Method Between Remote Sensing Images and AIS Data by Fan Li, Kun Yu, Chao Yuan, Yichen Tian, Guang Yang, Kai Yin, Youguang Li

“…The association accuracy of the multi-feature association algorithm is 91.74% in optical image and AIS data matching, and 91.33% in SAR image and AIS data matching. …”
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Research and Application of SURF and Gray Difference in Detection of Small Modulus Plastic Gear Defect by Yang Ya, Tao Hongyan, Yu Chengbo

“…The FLANN（ Fast library for approximate nearest neighbors） algorithm is used to match the detected SURF（ Speeded up robust features） descriptors. …”
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MFT-Reasoning RCNN: A Novel Multi-Stage Feature Transfer Based Reasoning RCNN for Synthetic Aperture Radar (SAR) Ship Detection by Siyu Zhan, Muge Zhong, Yuxuan Yang, Guoming Lu, Xinyu Zhou

“…Conventional ship detection using synthetic aperture radar (SAR) is typically limited to fully focused spatial features of the ship target in SAR images. …”
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