Detecting eavesdropping nodes in the power Internet of Things based on Kolmogorov-Arnold networks. by Rong Wang, Weibin Jiang, Yanjin Shen, Qiqing Yue, Kan-Lin Hsiung

“…Traditional eavesdropping detection methods struggle to adapt to complex and dynamic attack patterns, necessitating the exploration of more intelligent and efficient anomaly localization approaches. …”
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Advances in research on novel technologies for the detection of exogenous contaminants in traditional Chinese medicine by Ziyu Guo, Junyao Li, Lina Zeng, Ping Wang, Meifang Li, Chang Su, Shuhong Wang

“…Exogenous contaminants in traditional Chinese medicine (TCM), including pesticide residues, heavy metals, mycotoxins, and sulfur dioxide residues, pose significant risks to human health and environmental safety. Conventional detection methods are limited by insufficient sensitivity, complex sample preparation, and challenges in multi-residue analysis, compromising accuracy and efficiency. …”
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An optimized stacking-based TinyML model for attack detection in IoT networks. by Anshika Sharma, Shalli Rani, Mohammad Shabaz

“…With the expansion of Internet of Things (IoT) devices, security is an important issue as attacks are constantly gaining more complex. Traditional attack detection methods in IoT systems have difficulty being able to process real-time and access limitations. …”
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CP-YOLO: An Algorithm for Cigarette Pack Defects Detection Based on CCD Images by Peng Dong, Weihua Feng, Rui Wang, Mingyan Zhang, Qunye Hong, Yongsheng Wang, Di Wang, Guohao Zong

“…The failure to detect defective packs promptly may affect production efficiency and material consumption. …”
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Indocyanine Green and Arginine-Glycine-Aspartic Acid Complex Used in Intraoperative Visualization during Resection of Bladder Tumour by Li Peng, I. R. Kabirov, A. R. Kasinskaya, Jiaqi Wang, Wanhai Xu, E. K. Zhuk, R. A. Nuralieva

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Ensemble learning for multi-class COVID-19 detection from big data. by Sarah Kaleem, Adnan Sohail, Muhammad Usman Tariq, Muhammad Babar, Basit Qureshi

“…Although existing techniques are useful for detecting COVID-19 using X-rays, there is a need for further improvement in efficiency, particularly in terms of training and execution time. …”
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Lightweight Pyramid Cross-Attention Network for No-Service Rail Surface Defect Detection by Sixu Guo, Jiyou Fei, Liying Wang, Hua Li, Xiaodong Liu

“…Vision-based rail defect detection plays a crucial role in ensuring the safety and efficiency of railway transportation systems. …”
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Vehicle detection and classification for traffic management and autonomous systems using YOLOv10 by Anning Ji, Xintao Ma

“…Our approach leverages the advantages of each method to enhance detection accuracy and efficiency, especially in complex traffic scenarios. …”
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Detecting Alzheimer's Based on MRI Medical Images by Using External Attention Transformer by Farrel Ardannur Deswanto, Isman Kurniawan

“…It enhances image classification by using two shared external memories and an attention mechanism that filters out redundant information for improved performance and efficiency. The aim of this research is to evaluate and compare the performance of the baseline Convolutional Neural Network (CNN) model, the Vision Transformer (ViT) model, and the EAT model in detecting Alzheimer's using a dataset of 6400 brain MRI images. …”
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Multimodal image fusion for ich detection and classification using parallel Dl models by Sri Sangepu Nagaraju, S. Prince Mary, V. Pavani Chandra, Nandam Gayatri

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Research on foreign object intrusion detection in railway tracks based on MSL-YOLO by Hongxia Niu, Dingchao Feng, Tao Hou

“…This integration improves multi-scale feature representation and model efficiency. In addition, a Lightweight Shared Convolutional Detection Head (LSCD) is employed to replace the original head, reducing complexity while maintaining detection accuracy. …”
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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…First, a channel and spatial attention mechanism is introduced to improve the network’s capability to extract target features, significantly enhancing grasp detection performance in complex backgrounds. Second, an efficient attention module search strategy is proposed to replace traditional fully connected layer structures, which not only increases detection accuracy but also reduces computational overhead. …”
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Fault Detection in Gearboxes Using Fisher Criterion and Adaptive Neuro-Fuzzy Inference by Houssem Habbouche, Tarak Benkedjouh, Yassine Amirat, Mohamed Benbouzid

“…Consequently, deploying expert methods for fault detection and diagnosis is crucial to ensuring the reliability and efficiency of these systems. …”
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YOLO-HVS: Infrared Small Target Detection Inspired by the Human Visual System by Xiaoge Wang, Yunlong Sheng, Qun Hao, Haiyuan Hou, Suzhen Nie

“…The experimental results demonstrate that the proposed approach exhibits enhanced robustness in detecting targets under severe occlusion and low SNR conditions, while enabling efficient real-time infrared small target detection.…”
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CSF-YOLO: A Lightweight Model for Detecting Grape Leafhopper Damage Levels by Chaoxue Wang, Leyu Wang, Gang Ma, Liang Zhu

“…The model employs FasterNet as the backbone network to enhance computational efficiency and reduce model complexity. It substitutes for the nearest-neighbor upsampling with CARAFE to improve small target detection capabilities. …”
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Research on downhole drilling target detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…The multicore initiator module C2f_PKI is employed to replace C2f as the Backbone network to accelerate target detection and reduce model complexity. By incorporating FDPN and DASI fusion modules into the Head module section, the aim is to reduce model complexity and enhance detection accuracy. …”
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A Novel Metaheuristic-Based Methodology for Attack Detection in Wireless Communication Networks by Walaa N. Ismail

“…The unique characteristics of 5G networks, while enabling advanced communication, present challenges in distinguishing between legitimate and malicious traffic, making it more difficult to detect anonymous traffic. Current methodologies for intrusion detection within 5G communication exhibit limitations in accuracy, efficiency, and adaptability to evolving network conditions. …”
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Detection of weeds in vegetables using image classification neural networks and image processing by Huiping Jin, Kang Han, Kang Han, Hongting Xia, Bo Xu, Xiaojun Jin

“…However, the wide variety of weed types and their complex distribution creates difficulties in rapid and accurate weed detection. …”
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Optimizing RetinaNet anchors using differential evolution for improved object detection by Asaad Mohammed, Hosny M. Ibrahim, Nagwa M. Omar

“…It has two primary types: one-stage detectors known for their high speed and efficiency, and two-stage detectors, which offer higher accuracy but are often slower due to their complex architecture. …”
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AFHNet: Attention-Free Hybrid Network for Salient Object Detection in Underwater Images by Qian Tang, Zhen Wang, Xuqi Wang, Shan-Wen Zhang

“…However, traditional machine vision and deep learning approaches face notable challenges in complex underwater environments due to issues such as light attenuation, scattering, motion blur, color distortion, noise, low contrast, and multipath effects, which severely affect detection accuracy. …”
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