Real-Time Polarimetric Imaging and Enhanced Deep Learning Model for Automated Defect Detection of Specular Additive Manufacturing Surfaces by Dingkang Li, Xing Peng, Hongbing Cao, Yuanpeng Xie, Shiqing Li, Xiang Sun, Xinjie Zhao

“…While machine learning and neural network algorithms have recently achieved significant advancements in innovative applications for AM defect detection, practical implementations still face challenges, including insufficient detection accuracy and poor system robustness. …”
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A Lightweight Classification Algorithm for External Sources of Interference in IEEE 802.15.4-Based Wireless Sensor Networks Operating at the 2.4 GHz by Sven Zacharias, Thomas Newe, Sinead O'Keeffe, Elfed Lewis

“…This lightweight algorithm uses the energy detection (ED) feature (the feature behind received signal strength indication (RSSI)) of an IEEE 802.15.4-compliant radio. …”
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Analysis of vehicle and pedestrian detection effects of improved YOLOv8 model in drone-assisted urban traffic monitoring system. by Huili Dou, Sirui Chen, Fangyuan Xu, Yuanyuan Liu, Hongyang Zhao

“…This study proposes an improved YOLOv8 model for vehicle and pedestrian detection in urban traffic monitoring systems. In order to improve the detection performance of the model, we introduced a multi-scale feature fusion module and an improved non-maximum suppression (NMS) algorithm based on the YOLOv8 model. …”
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Unsupervised Rural Flood Mapping from Bi-Temporal Sentinel-1 Images Using an Improved Wavelet-Fusion Flood-Change Index (IWFCI) and an Uncertainty-Sensitive Markov Random Field (US... by Amin Mohsenifar, Ali Mohammadzadeh, Sadegh Jamali

“…In the first stage, the proposed IWFCI was compared to a number of state-of-the-art (SOTA) CIs, and the second stage compared USMRF to the SOTA change detection algorithms. From the experimental results in the first stage, the proposed IWFCI, yielding an average F-score of 86.20%, performed better than SOTA CIs. …”
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Exhaled volatile organic compounds as novel biomarkers for early detection of COPD, asthma, and PRISm: a cross-sectional study by Jiaxin Tian, Qiurui Zhang, Minhua Peng, Leixin Guo, Qianqian Zhao, Wei Lin, Sitong Chen, Xuefei Liu, Simin Xie, Wenxin Wu, Yijie Li, Junqi Wang, Jin Cao, Ping Wang, Min Zhou

“…We identified nine VOCs distinguishing COPD patients from healthy controls, nine VOCs differentiating the PRISm population from healthy controls, five VOCs separating asthma patients from healthy controls, five VOCs distinguishing COPD patients from asthma patients, and seven VOCs differentiating the PRISm population from asthma patients based on breathomics feature selection. We utilized five algorithms to establish diagnostic models and selected the optimal one among them. …”
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Machine Learning Framework for Early Detection of Chronic Kidney Disease Stages Using Optimized Estimated Glomerular Filtration Rate by Samit Kumar Ghosh, Namareq Widatalla, Ahsan H. Khandoker

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A Novel Detection-and-Replacement-Based Order-Operator for Differential Evolution in Solving Complex Bound Constrained Optimization Problems by Sichen Tao, Sicheng Liu, Shoya Ohta, Ruihan Zhao, Zheng Tang, Yifei Yang

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Tomato Ripening Detection in Complex Environments Based on Improved BiAttFPN Fusion and YOLOv11-SLBA Modeling by Yan Hao, Lei Rao, Xueliang Fu, Hao Zhou, Honghui Li

“…Lastly, the feature separability of comparable categories is significantly enhanced by the addition of the auxiliary detection head DetectAux. …”
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From Tweets to Threats: A Survey of Cybersecurity Threat Detection Challenges, AI-Based Solutions and Potential Opportunities in X by Omar Alsodi, Xujuan Zhou, Raj Gururajan, Anup Shrestha, Eyad Btoush

“…The findings indicate that current studies often lack comprehensive evaluations of critical aspects such as prediction scope, types of cybersecurity threats, feature extraction techniques, algorithm complexity, information summarization levels, scalability over time, and performance measurements. …”
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Fault Prediction of Hydropower Station Based on CNN-LSTM-GAN with Biased Data by Bei Liu, Xiao Wang, Zhaoxin Zhang, Zhenjie Zhao, Xiaoming Wang, Ting Liu

“…Meanwhile, a multi-scale feature extraction network with time–frequency information is designed to improve the accuracy of fault detection. …”
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A Lightweight SAR Ship Detection Network Based on Deep Multiscale Grouped Convolution, Network Pruning, and Knowledge Distillation by Boyi Hu, Hongxia Miao

“…Therefore, a lightweight algorithm for SAR ship detection is designed in this article. …”
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WPD-ResNeSt: Substation Station Level Network Anomaly Traffic Detection Based on Deep Transfer Learning by Ting Yang, Yucheng Hou, Yachuang Liu, Feng Zhai, Rongze Niu

“…The existing substation network analyzers and flow anomaly detection algorithms are usually based on threshold determination, which cannot reflect the inherent characteristics of substation automation flow based on IEC 61850 and have low detection accuracy. …”
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A Lightweight Method for Road Defect Detection in UAV Remote Sensing Images with Complex Backgrounds and Cross-Scale Fusion by Wenya Zhang, Xiang Li, Lina Wang, Danfei Zhang, Pengfei Lu, Lei Wang, Chuanxiang Cheng

“…Moreover, the CAA attention mechanism is employed to strengthen the model’s global feature extraction abilities; (2) a cross-scale feature fusion strategy known as GFPN is developed to tackle the problem of diverse target scales in road damage detection; (3) to reduce computational resource consumption, a lightweight detection head called EP-Detect has been specifically designed to decrease the model’s computational complexity and the number of parameters; and (4) the model’s localization capability for road damage targets is enhanced by integrating an optimized regression loss function called WiseIoUv3. …”
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An Analysis of Arterial Pulse Wave Time Features and Pulse Wave Velocity Calculations Based on Radial Electrical Bioimpedance Waveforms in Patients Scheduled for Coronary Catheteri... by Kristina Lotamõis, Tiina Uuetoa, Andrei Krivošei, Paul Annus, Margus Metshein, Marek Rist, Sulev Margus, Mart Min, Gert Tamberg

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Robust Multi-Input Multi-Output Analysis for Crop Row Segmentation and Furrow Line Detection in Diverse Agricultural Fields by Muhammad Ibrahim Zain Ul Abideen, Dewa Made Sri Arsa, Talha Ilyas, Hyunggi Jo, Sang Cheol Kim, Hyongsuk Kim

“…Our algorithm utilizes RGB and depth images, processed through a dual encoder that combines their features. …”
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Advanced video anomaly detection using 2D CNN and stacked LSTM with deep active learning-based model by ANOOPA S, Dr Salim A, Dr Nadera Beevi S

“…An active learning-based end-to-end system with full use of both spatial and temporal features from the input videos is proposed. The model combines the use of 2DCNN and Stacked LSTM to extract frame-level features through an improved anisotropic Gunnar Farneback Optical Flow algorithm. …”
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Empowering Healthcare: TinyML for Precise Lung Disease Classification by Youssef Abadade, Nabil Benamar, Miloud Bagaa, Habiba Chaoui

“…Our data preprocessing included bandpass filtering and feature extraction through Mel-Frequency Cepstral Coefficients (MFCCs). …”
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An adaptive prediction method for ultra-short-term generation power of power system based on the improved long- and short-term memory network of sparrow algorithm by Peipei Yang, Zhidong Chen, Wen Tang, Zongyang Liu, Bingrui He

“…The methodology involves the following steps: (1) Collecting historical ultra-short-term power generation data from photovoltaic systems, where outlier detection and data cleaning are performed using horizontal processing methods; (2) Applying Pearson correlation analysis to identify key meteorological factors significantly influencing power output as feature inputs; (3) Developing an Adaptive Sparrow Search Algorithm (ASSA) by dynamically adjusting the quantities of discoverers and followers in traditional SSA; (4) Optimizing LSTM network parameters through ASSA to enhance prediction accuracy. …”
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Automated Detection of Tailing Impoundments in Multi-Sensor High-Resolution Satellite Images Through Advanced Deep Learning Architectures by Lin Qin, Wenyue Song

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A feasibility study of an improved procedure for using EEG to detect brain responses to imagery instruction in patients with disorders of consciousness. by Anna Lisa Mangia, Marco Pirini, Laura Simoncini, Angelo Cappello

“…The proposed procedure uses feature selection based on a nested-leave-one-out algorithm to reduce the number of electrodes required. …”
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