YOLO-CSMD: Integrating Improved Convolutional Techniques for Manhole Cover Defect Detection by Zhiwang Xu, Haowei Luo, Huijie Zhu, Wanfa Sun, Shengying Yang

“…Recent detection algorithms for manhole cover defects exhibit limited detection capabilities, which frequently encounter the issue of missed detection. …”
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Developing a Machine Vision System to Detect Weeds from Potato Plant by Yousef Abbaspour Gılandeh, Hossein Javadıkıa, Sajad Sabzı

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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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Miniaturized Near-Infrared Analyzer for Quantitative Detection of Trace Water in Ethylene Glycol by Qunling Luo, Zhiqiang Guo, Danping Lin, Boxue Chang, Yinlan Ruan

“…To address the limitations of a traditional Fourier-transform infrared (FTIR) spectrometer, including its bulky size, high cost, and unsuitability for on-site industrial detection, this study developed a Fourier-transform near-infrared (FT-NIR) absorption testing system utilizing Micro-Electro-Mechanical System (MEMS) technology for detecting trace water content in ethylene glycol. …”
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Ensemble-based multiclass lung cancer classification using hybrid CNN-SVD feature extraction and selection method. by Md Sabbir Hossain, Niloy Basak, Md Aslam Mollah, Md Nahiduzzaman, Mominul Ahsan, Julfikar Haider

“…The extracted features were then processed by a set of ML algorithms along with a voting ensemble approach. …”
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DCW-YOLO: An Improved Method for Surface Damage Detection of Wind Turbine Blades by Li Zou, Anqi Chen, Chunzi Li, Xinhua Yang, Yibo Sun

“…In light of these challenges, a novel model named DCW-YOLO for surface damage detection of WTBs is proposed in this research, which leverages image data collected by unmanned aerial vehicles (UAVs) and the YOLOv8 algorithm for image analysis. …”
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Advanced fault detection in photovoltaic panels using enhanced U-Net architectures by Khalfalla Awedat, Gurcan Comert, Mustafa Ayad, Abdulmajid Mrebit

“…Fault detection in photovoltaic (PV) panels using thermal images remains a significant challenge due to the complexity of thermal patterns, environmental noise, and the subtle nature of anomalies. …”
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Cumulative confidence-driven task offloading for object detection in maritime Internet of Things by Yanglong Sun, Wenqian Luo, Weijian Xu, Qiang Mei, Haixia Peng, Linhai Wei

“…However, the dynamic marine network and environmental interference in feature extraction adversely affect detection accuracy and cause delay. …”
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YOLO-RGDD: A Novel Method for the Online Detection of Tomato Surface Defects by Ziheng Liang, Tingting Zhu, Guang Teng, Yajun Zhang, Zhe Gu

“…The experimental results show that the average precision, recall, and F1-score of the proposed YOLO-RGDD model for tomato defect detection reach 88.5%, 85.7%, and 87.0%, respectively, surpassing advanced object recognition detection algorithms. …”
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Tomato leaf disease detection method based on improved YOLOv8n by Ming Chen, Chunping Wang, Chengwei Liu, Ying Yu, Yuan Yuan, Jiaxuan Ma, Kaisheng Zhang

“…During the upsampling process, we adopt the Dysample upsampling operator, optimizing the quality of feature map reconstruction and improving detection resolution through a refined upsampling strategy. …”
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Review of Surface-Defect Detection Methods for Industrial Products Based on Machine Vision by Quan Wang, Mengnan Wang, Jiadong Sun, Deji Chen, Pei Shi

“…Traditional methods consist of image preprocessing, segmentation, and feature extraction. Machine learning methods are divided into point-distance-based, hyperplane-based, tree-based, and neural network-based classification algorithms. …”
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Modality-based Modeling with Data Balancing and Dimensionality Reduction for Early Stunting Detection by Yohanes Setiawan, Mohammad Hamim Zajuli Al Faroby, Mochamad Nizar Palefi Ma’ady, I Made Wisnu Adi Sanjaya, Cisa Valentino Cahya Ramadhani

“…The main contributions of this research are the development of a comprehensive framework for modality-based analysis, the application of advanced data preprocessing techniques, and the comparison of various machine learning algorithms to identify the best model for stunting detection. …”
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Traffic Sign Detection via Improved Sparse R-CNN for Autonomous Vehicles by Tianjiao Liang, Hong Bao, Weiguo Pan, Feng Pan

“…There is still a mismatch problem between the existing detection algorithm and its practical application in real traffic scenes, which is mainly due to the detection accuracy and data acquisition. …”
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Detection of Apple Proliferation Disease Using Hyperspectral Imaging and Machine Learning Techniques by Uwe Knauer, Sebastian Warnemünde, Patrick Menz, Bonito Thielert, Lauritz Klein, Katharina Holstein, Miriam Runne, Wolfgang Jarausch

“…Therefore, the potential of hyperspectral imaging in combination with data analysis by machine learning algorithms was investigated to detect the symptoms solely based on the spectral signature of collected leaf samples. …”
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A lightweight deep-learning model for parasite egg detection in microscopy images by Wenbin Xu, Qiang Zhai, Jizhong Liu, Xingyu Xu, Jing Hua

“…Abstract Background Intestinal parasitic infections are still a serious public health problem in developing countries, and the diagnosis of parasitic infections requires the first step of parasite/egg detection of samples. Automated detection can eliminate the dependence on professionals, but the current detection algorithms require large computational resources, which increases the lower limit of automated detection. …”
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Anomaly detection with domain specific shapelet learning for sucker rod pump system by Xiangyu Li, Zhupei Liao, Chunhua Yuan

“…This paper proposes an unsupervised end-to-end learning algorithm designed for SRPS anomaly detection, denoted Anomaly Detection with Domain-specific Shapelet Learning algorithm (AD-DSL). …”
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Construction of a feature gene and machine prediction model for inflammatory bowel disease based on multichip joint analysis by Yan Chaosheng, Sun Haowen, Rao Jingjing, Dai Yuanyuan, Duan Wenhui, Sheng Yingyue, Xue Yuzheng

“…On the basis of methods such as artificial neural networks (ANNs), machine learning techniques, and the SHAP model, we developed a diagnostic model for IBD. To select genetic features, we utilized three machine learning algorithms, namely, least absolute shrinkage and selection operator (LASSO), support vector machine (SVM), and random forest (RF), to identify differentially expressed genes. …”
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Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning by Shenlan Zhang, Shaojie Wu, Liqiang Chen, Pengxin Guo, Xincheng Jiang, Hongcheng Pan, Yuhong Li

“…Subsequently, to effectively improve detection accuracy while reducing model parameters and computational load, we implemented several improvements to the deep learning algorithm, including the MGFF (Multi-Scale Grouped Feature Fusion) module, the LSKA-SPPF (Large Separable Kernel Attention-Spatial Pyramid Pooling-Fast) module, and the GNDCDH (Group Norm Detail Convolution Detection Head). …”
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Cluster Workload Allocation: A Predictive Approach Leveraging Machine Learning Efficiency by Leszek Sliwko

“…This research investigates how Machine Learning (ML) algorithms can assist in workload allocation strategies by detecting tasks with node affinity operators (referred to as constraint operators), which constrain their execution to a limited number of nodes. …”
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Whispers in the air: Designing acoustic classifiers to detect fruit flies from afar by Alia Khalid, Muhammad Latif Anjum, Salman Naveed, Wajahat Hussain

“…Our proposed method generalizes over different classifiers and features. Our algorithm provides robust detection and classification of multiple bugs, over longest ranges reported, using simple microphones. …”
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