A Defect Detection Algorithm for Optoelectronic Detectors Utilizing GLV-YOLO by Xinfang Zhao, Qinghua Lyu, Hui Zeng, Zhuoyi Ling, Zhongsheng Zhai, Hui Lyu, Saffa Riffat, Benyuan Chen, Wanting Wang

“…Compared to other methods, our approach outperforms them in both performance and efficiency, fulfilling the real-time and precise defect detection needs of photodetectors.…”
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Multimodal-Based Non-Contact High Intraocular Pressure Detection Method by Zibo Lan, Ying Hu, Shuang Yang, Jiayun Ren, He Zhang

“…To address these limitations, we present a multi-modal framework incorporating CycleGAN for data augmentation, Swin Transformer for visual feature extraction, and the Kolmogorov–Arnold Network (KAN) for efficient fusion of heterogeneous data. KAN approximates complex nonlinear relationships with fewer parameters, making it effective in small-sample scenarios with intricate variable dependencies. …”
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Lightweight Detection of Train Underframe Bolts Based on SFCA-YOLOv8s by Zixiao Li, Jinjin Li, Chuanlong Zhang, Huajun Dong

“…To achieve efficient detection, a lightweight detection method based on SFCA-YOLOv8s is proposed. …”
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Artificial Intelligence in Wind Turbine Fault Detection and Diagnosis: Advances and Perspectives by Nejad Alagha, Anis Salwa Mohd Khairuddin, Zineddine N. Haitaamar, Obada Al-Khatib, Jeevan Kanesan

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Copper Nodule Defect Detection in Industrial Processes Using Deep Learning by Zhicong Zhang, Xiaodong Huang, Dandan Wei, Qiqi Chang, Jinping Liu, Qingxiu Jing

“…The surface of cathodic copper plates is often affected by various electrolytic process factors, resulting in the formation of nodule defects that significantly impact surface quality and disrupt the downstream production process, making the prompt detection of these defects essential. At present, the detection of cathode copper plate nodules is performed by manual identification. …”
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Research on Fire Smoke Detection Algorithm Based on Improved YOLOv8 by Tianxin Zhang, Fuwei Wang, Weimin Wang, Qihao Zhao, Weijun Ning, Haodong Wu

“…Fire has consistently posed a significant disaster risk worldwide. Current fire detection methods primarily rely on traditional physical sensors such as light, smoke, and temperature detectors, which often struggle in complex environments. …”
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Personalizing Seizure Detection for Individual Patients by Optimal Selection of EEG Signals by Rosanna Ferrara, Martino Giaquinto, Gennaro Percannella, Leonardo Rundo, Alessia Saggese

“…This interpretable, patient-specific method enables the development of personalized, efficient, and compact wearable devices for reliable seizure detection in everyday life.…”
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Damage Detection of Steel Roof Systems Using Planet Optimization Algorithm by Thanh Sang-To, Van The Huy-Nguyen, Samir Khatir, The Vi-Huynh, Hoang Le-Minh, Thanh Cuong-Le

“…Also, the results proved that this technique provides an efficient solution to the complex problem with many constraints in unknown search space.…”
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Machine Learning-Based Network Anomaly Detection: Design, Implementation, and Evaluation by Pilar Schummer, Alberto del Rio, Javier Serrano, David Jimenez, Guillermo Sánchez, Álvaro Llorente

“…<b>Background:</b> In the last decade, numerous methods have been proposed to define and detect outliers, particularly in complex environments like networks, where anomalies significantly deviate from normal patterns. …”
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Deep Learning in Defect Detection of Wind Turbine Blades: A Review by Katleho Masita, Ali N. Hasan, Thokozani Shongwe, Hasan Abu Hilal

“…Additionally, transfer learning and attention mechanisms have been instrumental in enhancing the precision and speed of defect detection, enabling real-time applications. Notable approaches like YOLO (You Only Look Once) and its variants have shown exceptional performance in detecting defects with varying scales and complexities, leveraging innovations such as feature pyramid networks and efficient loss functions. …”
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PS-YOLO: A Lighter and Faster Network for UAV Object Detection by Han Zhong, Yan Zhang, Zhiguang Shi, Yu Zhang, Liang Zhao

“…The operational environment of UAVs poses unique challenges for object detection compared to conventional methods. When UAVs capture remote sensing images from elevated altitudes, objects often appear minuscule and can be easily obscured by complex backgrounds. …”
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Cardiovascular Disease Detection through Innovative Imbalanced Learning and AUC Optimization by Karthikeyan Palanisamy, Krishnaveni Krishnasamy, Praba Venkadasamy

“…Furthermore, we have incorporated a tailored Differential Evolution (DE) algorithm designed to navigate the complex hyperparameter space with finesse. The performance of this model was rigorously evaluated using comprehensive data from a medical survey conducted in 2012, which included an extensive cohort of 26,002 athletes. …”
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Optimized driver fatigue detection method using multimodal neural networks by Shengli Cao, Peihua Feng, Wei Kang, Zeyi Chen, Bo Wang

“…These results highlight the advantages of the multimodal feature-coupled model in addressing the challenges of driver fatigue detection, making it a valuable tool for enhancing road safety through advanced, efficient monitoring systems in vehicles.…”
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Detecting microcephaly and macrocephaly from ultrasound images using artificial intelligence by Abraham Keffale Mengistu, Bayou Tilahun Assaye, Addisu Baye Flatie, Zewdie Mossie

“…Objective This study aims to develop a fetal head abnormality detection model from ultrasound images via deep learning. …”
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Cloud-edge collaborative data anomaly detection in industrial sensor networks. by Tao Yang, Xuefeng Jiang, Wei Li, Peiyu Liu, Jinming Wang, Weijie Hao, Qiang Yang

“…Industrial sensor networks exhibit heterogeneous, federated, large-scale, and intelligent characteristics due to the increasing number of Internet of Things (IoT) devices and different types of sensors. Efficient and accurate anomaly detection of sensor data is essential for guaranteeing the system's operational reliability and security. …”
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Detection of Hydrophobicity Grade of Composite Insulators Based on MDC‐YOLO Algorithm by Shaotong Pei, Weiqi Wang, Chenlong Hu, Haichao Sun, Keyu Li, Mianxiao Wu, Bo Lan

“…ABSTRACT In the field of power equipment inspection, the aging condition of composite insulators is often determined by the detection of water repellency. However, the existing detection methods are difficult to effectively extract the water repellency level features in the complex background, and it is difficult to meet the real‐time requirements. …”
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Improved YOLOv8-Based Algorithm for Citrus Leaf Disease Detection by Zhengbing Zheng, Yibang Zhang, Luchao Sun

“…Furthermore, it strikes an effective balance between enhancing detection accuracy, reducing model complexity, and maintaining a lightweight architecture, making them well-suited for efficient citrus leaf disease detection.…”
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Hyperspectral Simultaneous Anomaly Detection and Denoising: Insights From Integrative Perspective by Minghua Wang, Lianru Gao, Longfei Ren, Xian Sun, Jocelyn Chanussot

“…However, scholars have been addicted to developing numerous complex methods for separable two-stage denoising and anomaly detection (AD) tasks over the past years, rarely paying attention to the real effect of noises for subsequent intelligent interpretation. …”
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Detecting faults in electronic combustion engine control systems by acoustic parameters by V. D. Gabidulin, V. N. Dobromirov

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Explainable MRI-Based Ensemble Learnable Architecture for Alzheimer’s Disease Detection by Opeyemi Taiwo Adeniran, Blessing Ojeme, Temitope Ezekiel Ajibola, Ojonugwa Oluwafemi Ejiga Peter, Abiola Olayinka Ajala, Md Mahmudur Rahman, Fahmi Khalifa

“…With the advancements in deep learning methods, AI systems now perform at the same or higher level than human intelligence in many complex real-world problems. The data and algorithmic opacity of deep learning models, however, make the task of comprehending the input data information, the model, and model’s decisions quite challenging. …”
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