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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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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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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PCES-YOLO: High-Precision PCB Detection via Pre-Convolution Receptive Field Enhancement and Geometry-Perception Feature Fusion by Heqi Yang, Junming Dong, Cancan Wang, Zhida Lian, Hui Chang

“…Printed circuit board (PCB) defect detection faces challenges like small target feature loss and severe background interference. …”
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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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YOLO-FDCL: Improved YOLOv8 for Driver Fatigue Detection in Complex Lighting Conditions by Genchao Liu, Kun Wu, Wei Lan, Yunjie Wu

“…Additionally, by incorporating the concept of structural re-parameterization, RepFPN is introduced into the neck section of the algorithm to strengthen the network’s multi-scale feature fusion capabilities, further improving the model’s detection performance. …”
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MFFNet: a building change detection method based on fusion of spectral and geometric information by Zhihao Guo, Jianping Pan, Peng Xie, Ling Zhu, Chen Qi, Xunxun Wang, Yihan Yang, Yan Wang, Huijuan Zhang, Zhaohui Ren

“…However, when using remote sensing images, shadows, vegetation and objects with similar spectral and morphological characteristics as buildings can cause false detections, omissions and incomplete patch edges. To address this issue, we develop the multiscale feature fusion network for dual-modal data (MFFNet), which has two main aspects: (1) The multi-dual-modal feature fusion module detects changes in features with similar spectral and morphological characteristics as buildings. …”
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PC3D-YOLO: An Enhanced Multi-Scale Network for Crack Detection in Precast Concrete Components by Zichun Kang, Kedi Gu, Andrew Yin Hu, Haonan Du, Qingyang Gu, Yang Jiang, Wenxia Gan

“…Crack detection in precast concrete components aims to achieve precise extraction of crack features within complex image backgrounds. …”
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An exploratory analysis of longitudinal artificial intelligence for cognitive fatigue detection using neurophysiological based biosignal data by Sameer Nooh, Mahmoud Ragab, Rania Aboalela, Abdullah AL-Malaise AL-Ghamdi, Omar A. Abdulkader, Ghadah Alghamdi

“…Furthermore, the binary olympiad optimization algorithm (BOOA)-based feature selection is utilized to extract the most informative features, reducing the data dimensionality. …”
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Accurate detection of critical LLFs and LGFs in PV arrays based on deep reinforcement learning using proximal policy optimization (PPO) by Sherko Salehpour, Aref Eskandari, Amir Nedaei, Mohammad Gholami, Mohammadreza Aghaei

“…To address these challenges, the present paper proposes a deep reinforcement learning (DRL)-based model to detect, classify, and assess the severity of all and specifically critical LLFs and LGFs in PV arrays using the proximal policy optimization (PPO) algorithm. …”
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Computer Vision for Substrate Detection in High‐Throughput Biomaterial Screens Using Bright‐Field Microscopy by Robert Owen, Aishah Nasir, Mahetab H. Amer, Chenxue Nie, Xuan Xue, Laurence Burroughs, Chris Denning, Ricky D. Wildman, Faraz A. Khan, Morgan R. Alexander, Felicity R. A. J. Rose

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MF-YOLOv10: Research on the Improved YOLOv10 Intelligent Identification Algorithm for Goods by Quanwei Wang, Xiaoyang Wang, Jiayi Hou, Xuying Liu, Hao Wen, Ziya Ji

“…The algorithm significantly improves the feature extraction and detection capabilities by replacing the traditional IoU loss function with the MPDIoU and introducing the SCSA attention module. …”
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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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A Decision Support System For Early Stage Parkinson's Diagnosis from EEG Data Using Symbolic Mutual Information and KAC Features by Nurhan Gürsel Özmen, Neslihan Baki

“…Therefore, in this study, an efficient PD detection method from EEG data by using a new set of features is searched. …”
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Research on dimension measurement algorithm for parcel boxes in high-speed sorting system by Ning Dai, Jingchao Chen, Xudong Hu, Yanhong Yuan

“…In this paper, we propose a 3D localization algorithm for rectangular packaging boxes based on deep learning, and design a lightweight parcel box detection model, the Efficient Object detection Network (EODNet). …”
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MF-ShipNet: a multi-feature weighted fusion and PCA-SVM model for ship detection in remote sensing images by Jianfeng Li, Yibing Yang, Liutong Yang, Yang Zhao, Qinghua Luo, Chenxu Wang

“…Compared with the ship target detection algorithm based on HOG feature combined with SVM classifier, the F1-score is improved from 0.554 to 0.879. …”
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MicrocrackAttentionNext: Advancing Microcrack Detection in Wave Field Analysis Using Deep Neural Networks Through Feature Visualization by Fatahlla Moreh, Yusuf Hasan, Bilal Zahid Hussain, Mohammad Ammar, Frank Wuttke, Sven Tomforde

“…This study proposes an asymmetric encoder–decoder network with an adaptive feature reuse block for microcrack detection. The impact of various activation and loss functions are examined through feature space visualisation using the manifold discovery and analysis (MDA) algorithm. …”
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Optimized deep learning approach for lung cancer detection using flying fox optimization and bidirectional generative adversarial networks by Manal Abdullah Alohali, Hamed Alqahtani, Shouki A. Ebad, Faiz Abdullah Alotaibi, Venkatachalam K., Jaehyuk Cho

“…Computer-aided diagnosis (CAD) systems have significantly improved early cancer detection, but limitations such as high-dimensional feature sets and overfitting issues persist. …”
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Enhancing Intelligent Road Target Monitoring: A Novel BGS-YOLO Approach Based on the YOLOv8 Algorithm by Xingyu Liu, Yuanfeng Chu, Yiheng Hu, Nan Zhao

“…This integration overcomes the limitations in feature extraction and recognition found in existing target detection algorithms. …”
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EfficientNet-b0-Based 3D Quantification Algorithm for Rectangular Defects in Pipelines by Di Wu, Yong Hong, Jie Wang, Shaojun Wu, Zhihao Zhang, Yizhang Liu

“…This research introduces EffiTriDimNet (ETDN), a multi-task convolutional neural network that combines one-dimensional pipeline defect leakage detection data into a unified feature map while simultaneously measuring the three-dimensional characteristics of the defects. …”
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