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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Image-based maturity detection for selective cauliflower harvesting in field condition by Ajay Kushwah, P.K. Sharma, H.L. Kushwaha, Brij Bihari Sharma, Naseeb Singh, Ramineni Harsha Nag, Manojit Chowdhury, Nrusingh Charan Pradhan, Gopal Carpenter, Silpa Mandal, Ali Salem

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Apnea detection using wrist actigraphy in patients with heterogeneous sleep disorders by Xiaoman Xing, Sizhi Ai, Jihui Zhang, Rui Huang, Yaping Liu, Dongming Quan, Jiacheng Ma, Guoli Wu, Jiangen Xu, Yuan Zhang, Hongliang Feng, Wen-fei Dong

“…This study introduces an enhanced single-sensor-based OSA screening method, leveraging novel signal processing and machine learning to ensure accurate detection across diverse populations. Wrist actigraphy is a widely-used and energy-efficient tool for respiratory rate estimation. …”
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Lightweight obstacle detection for unmanned mining trucks in open-pit mines by Guangwei Liu, Jian Lei, Zhiqing Guo, Senlin Chai, Chonghui Ren

“…In addition, this paper also adopts the amplitude-based layer adaptive sparse pruning algorithm (LAMP) to further compress the model size while maintaining efficient detection performance. Through this pruning strategy, the model further reduces its dependence on computing resources while maintaining key performance. …”
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Detection of cucumber downy mildew spores based on improved YOLOv5s by Chen Qiao, Kaiyu Li, Xinyi Zhu, Jiaping Jing, Wei Gao, Lingxian Zhang

“…Consequently, developing a rapid, accurate, and efficient method for detecting cucumber downy mildew spores is critical for advancing disease control. …”
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DRCO: Dense-Label Refinement and Cross Optimization for Semi-Supervised Object Detection by Yunlong Qin, Yanjun Li, Feifan Ji, Yan Liu, Yu Wang, Ji Xiang

“…In semi-supervised object detection (SSOD), the methods based on dense pseudo-labeling bypass complex post-processing while maintaining competitive performance compared to the methods based on sparse pseudo-labeling. …”
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RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements by Tianyu Li, Xuanrui Xiong, Yuan Zhang, Xiaolin Fan, Yushu Zhang, Haihong Huang, Dan Hu, Mengting He, Zhanjun Liu

“…The complexity and variability of real-world road environments make the detection of densely occluded objects more challenging in autonomous driving scenarios. …”
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Efficient extraction of experimental data from line charts using advanced machine learning techniques by Wenjin Yang, Jie He, Xiaotong Zhang

“…Lastly, we present a method for automatically converting image data into structured JSON data, significantly enhancing the efficiency and accuracy of data extraction. Experimental results demonstrate that this method exhibits high efficiency and accuracy in handling complex charts, achieving an average extraction accuracy of 93% on public datasets, significantly surpassing the current state-of-the-art methods. …”
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Tear replacement by cationic emulsion in complex therapy of superficial punctate keratitis in hypotensively medicated glaucoma patients by S. V. Trufanov, S. A. Malozhen, D. A. Krakhmaleva, E. A. Pivin

“…The testing procedures and efficiency monitoring included biomicroscopy, Schirmer test, Norn test and evaluation of tear film osmolarity. …”
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