Recent advances in machine learning for defects detection and prediction in laser cladding process by X.C. Ji, R.S. Chen, C.X. Lu, J. Zhou, M.Q. Zhang, T. Zhang, H.L. Yu, Y.L. Yin, P.J. Shi, W. Zhang

“…Furthermore, it encapsulates prevalent machine learning models and algorithms employed for defect detection. The findings highlight the efficacy of machine learning algorithms in detecting defects within laser cladding coatings, while concurrently establishing correlations between feature signals, coating defects, and cladding processes. …”
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Benthos-DETR: a high-precision efficient network for benthic organisms detection by Weibo Rao, Gang Chen, Yifei Zhang, Jue Cang, Shusen Chen, Chenyang Wang

“…This study proposes Benthos-DETR, a benthic organisms detection network based on the RT-DETR network. In the backbone of Benthos-DETR network, the Efficient Block with the C2f module reinforces the shallow feature extraction operation in Benthos-DETR, enhancing the algorithm’s multi-scale perception. …”
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Improving Vertebral Fracture Detection in C-Spine CT Images Using Bayesian Probability-Based Ensemble Learning by Abhishek Kumar Pandey, Kedarnath Senapati, Ioannis K. Argyros, G. P. Pateel

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A Rapid Concrete Crack Detection Method Based on Improved YOLOv8 by Yongzhen Wang, Jiacong He

“…This study not only improves the accuracy and speed of crack detection but also significantly reduces the computational complexity of the model, advancing the development of lightweight and practical crack detection algorithms. …”
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Real-time classroom student behavior detection based on improved YOLOv8s by Xiaojing Sheng, Suqiang Li, Sixian Chan

“…However, the field still faces specific challenges, primarily concerning the accuracy of identifying student behaviors within complex and variable classroom environments, as well as the real-time capabilities of detection algorithms. To address these challenges, we propose an efficient and straightforward algorithm based on the YOLO architecture. …”
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YOLO-MES: An Effective Lightweight Underwater Garbage Detection Scheme for Marine Ecosystems by Chengxu Huang, Wenyuan Zhang, Beitian Zheng, Jiahao Li, Bochen Xie, Ruisi Nan, Zongming Tan, Baohua Tan, Neal N. Xiong

“…To address this issue, this paper introduces YOLO-MES, an innovative underwater debris detection algorithm that integrates a lightweight design and a feature enhancement mechanism to enable efficient model deployment while preserving high accuracy. …”
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An Equipment Identification Method Based on Lightweight CenterNet from Multivariate Features Fusion for Distribution Area by WANG Wenbin, FAN Ruixiang, DENG Zhixiang, WAN Junbiao, PAN Jianbing

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Comparison of Clustering Algorithms: Fuzzy C-Means, K-Means, and DBSCAN for House Classification Based on Specifications and Price by Dhendy Mardiansyah Putra, Ferian Fauzi Abdulloh

“…This study aims to compare the performance of three clustering algorithms, namely Fuzzy C-Means, K-Means, and DBSCAN, in grouping houses based on their specifications and prices. …”
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MDIGCNet: Multidirectional Information-Guided Contextual Network for Infrared Small Target Detection by Luping Zhang, Junhai Luo, Yian Huang, Fengyi Wu, Xingye Cui, Zhenming Peng

“…Experimental results on public datasets NUDT-SIRST, IRSTD-1k, and SIRST-Aug demonstrate that our algorithm outperforms other state-of-the-art methods in detection performance.…”
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BCSM-YOLO: An Improved Product Package Recognition Algorithm for Automated Retail Stores Based on YOLOv11 by Pingqing Hou, Shaoze Huang

“…To address YOLOv11’s limitations in supermarket scenarios, such as missed small targets and low positioning accuracy, this paper proposes BCSM-YOLO, an improved algorithm based on YOLOv11. Firstly, introducing the Space-to-Depth Convolution (SPD-Conv) can maximize the preservation of detailed information such as commodity texture and shape in the downsampling stage, which provides a rich information base for the subsequent feature extraction. …”
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A novel motion key frame extraction and video stream classification based on reinforcement learning and feature fusion by Hongbo Cui, Tao Feng, Jinhui Zheng

“…In order to solve the problem of missing detection and false detection caused by the inaccuracy of motion feature extraction in the existing video key frame extraction algorithms, a reinforcement learning and feature fusion for key frame extraction algorithm and video stream classification is proposed. …”
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Elevator fault precursor prediction based on improved LSTM-AE algorithm and TSO-VMD denoising technique. by Hao Cao, Xiaoyan Du

“…The robust capability of the VMD-BILSTM-AEAM algorithm to accurately process and analyze time-series data, even in the presence of noise, highlights its potential for broader applications in predictive maintenance and fault detection across various domains.…”
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Unsupervised Structural Damage Detection Technique Based on a Deep Convolutional Autoencoder by Zahra Rastin, Gholamreza Ghodrati Amiri, Ehsan Darvishan

“…The major focus of SHM studies in recent years has been on developing vibration-based damage detection algorithms and using machine learning, especially deep learning-based approaches. …”
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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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Detection of AI-Generated Texts: A Bi-LSTM and Attention-Based Approach by John Blake, Abu Saleh Musa Miah, Krzysztof Kredens, Jungpil Shin

“…This paper presents a novel algorithm that leverages cutting-edge machine-learning techniques to accurately and efficiently detect AI-generated texts. …”
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Detection of DDoS Attacks in SDN Switches with Deep Learning and Swarm Intelligence Approach by Mohsen Eghbali, Mohammadreza Mollkhalili Maybodi

“…Experimental results obtained in MATLAB, using the NSL-KDD dataset, demonstrate the proposed method’s effectiveness, achieving an accuracy of 99.34%, a sensitivity of 99.16%, and a precision of 98.93% in attack detection. The proposed method outperforms feature selection methods based on WOA, HHO, and AO algorithms, and deep learning methods like LSTM, RNN, and CNN, particularly in detecting DDoS attacks.…”
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DDFNet: A Dual-Domain Fusion Network for Robust Synthetic Speech Detection by Jing Lu, Qiang Zhang, Jialu Cao, Hui Tian

“…Existing methods primarily focus on either the time or frequency domain of speech, limiting their ability to generalize to new and diverse speech synthesis algorithms. In this work, we present a novel and scientifically grounded approach, the Dual-domain Fusion Network (DDFNet), which synergistically integrates features from both the time and frequency domains to capture complementary information. …”
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Transportation Mode Detection Using Learning Methods and Self-Contained Sensors: Review by Ilhem Gharbi, Fadoua Taia-Alaoui, Hassen Fourati, Nicolas Vuillerme, Zebo Zhou

“…Due to increasing traffic congestion, travel modeling has gained importance in the development of transportion mode detection (TMD) strategies over the past decade. Nowadays, recent smartphones, equipped with integrated inertial measurement units (IMUs) and embedded algorithms, can play a crucial role in such development. …”
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Rolling window for detecting multiple Chan signatures to diagnose excessive water production by Ahmed MohamedSalih Musa Hamdoon, A. P. Mohammed Abdalla Ayoub Mohammed, A. P. Khaled Abdalla Elraies

“…A successful interactive model with the rolling window feature was developed to track slope changes in Chan signatures, resulting in a 7–10% improvement in pattern detection accuracy compared to static features. …”
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Degradation Type-Aware Image Restoration for Effective Object Detection in Adverse Weather by Xiaochen Huang, Xiaofeng Wang, Qizhi Teng, Xiaohai He, Honggang Chen

“…Mainstream algorithms for adverse weather object detection enhance detection performance through image restoration methods. …”
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