Near Miss Detection Using Distancing Monitoring and Distance-Based Proximal Indicators by Lek Ming Lim, Lu Yang, Wen Zhu, Ahmad Sufril Azlan Mohamed, Majid Khan Majahar Ali

“…Despite efforts to improve road safety, accidents persist due to insufficient evidence from manual police reporting, non-optimized detection algorithms, and technical limitations in real-time video processing and modelling. …”
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Fault diagnosis method of mine hoist main bearing with small sample based on VAE-WGAN by Fan JIANG, Hongyan SONG, Xi SHEN, Zhencai ZHU, Shuman CHENG

“…VAE-WGAN was trained using the bearing dataset of the mine hoist simulation test bench to achieve the expansion and expansion of the small sample dataset. In order to improve the feature extraction ability and fault diagnosis accuracy of fault diagnosis models, based on the lightweight convolutional neural network MobileNetV2, the convolutional block attention mechanism CBAM is integrated into the deep feature mapping of MobileNetV2, and an attention mechanism convolutional classification network CBAM-MobileNetV2 is constructed. …”
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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

“…The increasing adoption of wind turbines as a key component of renewable energy generation necessitates the development of efficient and reliable maintenance strategies to ensure their optimal performance and safety. Among the most critical aspects of turbine maintenance is detecting and classifying defects in wind turbine blades, which are constantly exposed to extreme environmental conditions. …”
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On the academic ideology of “Sorting the gangue is sorting the images” by Hongwei MA, Ye ZHANG, Peng WANG, Xiangang CAO, Zhen NIE, Xiaorong WEI, Wenjian ZHOU, Mingzhen ZHANG

“…Coal gangue sorting is the most basic, effective, and important technical measure to improve coal quality. …”
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A deep neural network framework for estimating coastal salinity from SMAP brightness temperature data by Yidi Wei, Qing Xu, Qing Xu, Xiaobin Yin, Xiaobin Yin, Yan Li, Yan Li, Kaiguo Fan

“…Compared with SMAP SSS products, the baseline DNN demonstrates a reduction of 33.8% and 7.3% in RMSE in nearshore (dis ≤ 50 km) and offshore regions (50 km<dis ≤ 200 km), respectively. The specific models constructed for nearshore and offshore areas, as well as for the four seasons, further improves salinity retrieval accuracy, especially in nearshore regions, highlighting the effectiveness of regional and seasonal optimization strategies in complex coastal environments. …”
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Estimation and trend analysis of grassland aboveground biomass on the Qinghai-Xizang Plateau based on machine learning by Ruoqi Zhang, Qisheng Feng, Yonghui Zhang, Jingjing Mai, Tiangang Liang

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Enhancing Yield Estimation and Field Zoning Accuracy in Precision Agriculture Using Solar-Powered Drone-Based Remote Sensing by Abbas Haider Mohammed, Obaid Mohammed Kadhim, Vittalaiah A.

“…The system processes this data using advanced machine learning algorithms to forecast crop yields and generate detailed field zoning maps, enabling optimized resource allocation and improved farm management. …”
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Field measurement of atmospheric CO₂ column abundance based on portable laser heterodyne radiometer by Yong Wang, Yong Wang, Maolei Zhang, Maolei Zhang, Jiapeng Wang, Jiapeng Wang, Gang Wang, Gang Wang, Ruyue Cui, Ruyue Cui, Lei Dong, Lei Dong, Hongpeng Wu, Hongpeng Wu

“…Furthermore, a forward model based on line-by-line integration and an iterative fitting algorithm were employed to achieve high-precision CO₂ column abundance calculations. …”
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Revolutionizing Clear-Sky Humidity Profile Retrieval with Multi-Angle-Aware Networks for Ground-Based Microwave Radiometers by Yinshan Yang, Zhanqing Li, Jianping Guo, Yuying Wang, Hao Wu, Yi Shang, Ye Wang, Langfeng Zhu, Xing Yan

“…Here, we present a novel retrieval algorithm called AngleNet, a groundbreaking deep-learning model that leverages multi-angle BT observation from ground-based microwave radiometers (MWRs). …”
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A Framework for Autonomous UAV Navigation Based on Monocular Depth Estimation by Jonas Gaigalas, Linas Perkauskas, Henrikas Gricius, Tomas Kanapickas, Andrius Kriščiūnas

“…The solution utilizes a depth image estimation model to create an occupancy grid map of the surrounding area and uses an A* path planning algorithm to find optimal paths to end goals while navigating around the obstacles. …”
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Graph Based Cooperative Forwarding in Information Centric Vehicular Networks by Beri Surya Samantha, Nitul Dutta, Rajesh Mahadeva, Shashikant P. Patole, Gheorghita Ghinea

“…The prime objective of the algorithm is to reduce content retrieval time and optimize network overhead and throughput. …”
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Weed-crop dataset in precision agriculture: Resource for AI-based robotic weed control systemsMendeley Data by Arjun Upadhyay, Sunil G. C, Maria Villamil Mahecha, Joseph Mettler, Kirk Howatt, William Aderholdt, Michael Ostlie, Xin Sun

“…Effective weed management is crucial for maintaining optimal crop growth and achieve higher yield. Recent advancement in robotic technologies and advanced deep learning (DL) models is shaping the future of robotic weed control systems. …”
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Advancing Mental Health Care: Intelligent Assessments and Automated Generation of Personalized Advice via M.I.N.I and RoBERTa by Yuezhong Wu, Huan Xie, Lin Gu, Rongrong Chen, Shanshan Chen, Fanglan Wang, Yiwen Liu, Lingjiao Chen, Jinsong Tang

“…This paper integrates finite state machines, retrieval algorithms, semantic-matching models, and medical-knowledge graphs to design an innovative intelligent auxiliary evaluation tool and a personalized medical-advice generation application, aiming to improve the efficiency of mental health assessments and the provision of personalized medical advice. …”
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Semi-supervised anchorless single-engine grip detection by Yun Shi, Gang Zhang, Min Kong, Jie Fang

“…The extensive application of artificial intelligence in wireless communication, 3D reconstruction, and target location has successfully solved the modeling problem. Grasping specific objects in a stacked scene is a difficult task to achieve robot grasping. …”
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A novel hybrid deep learning approach for super-resolution and objects detection in remote sensing by Muhammad Asif, Mohammad Abrar, Faizan Ullah, Abdu Salam, Farhan Amin, Isabel de la Torre, Mónica Gracia Villar, Helena Garay, Gyu Sang Choi

“…This study proposes a robust object detection framework integrating super-resolution techniques with advanced feature extraction algorithms for remote sensing images. The hybrid model combines Advanced StyleGAN and Swin Transformer. …”
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Intelligent Reflecting Surface-Assisted Wireless Communication Using RNNs: Comprehensive Insights by Rana Tabassum, Mohammad Abrar Shakil Sejan, Md Habibur Rahman, Md Abdul Aziz, Hyoung-Kyu Song

“…In IRS-assisted communication systems, accurate channel estimation is crucial for optimizing signal transmission and achieving high spectral efficiency. …”
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Lightweight Brain Tumor Segmentation Through Wavelet-Guided Iterative Axial Factorization Attention by Yueyang Zhong, Shuyi Wang, Yuqing Miao, Tao Zhang, Haoliang Li

“…Conclusions: This study underscores the advantages of integrating frequency-domain analysis with optimized attention mechanisms, paving the way for scalable, high-performance medical image segmentation algorithms with broader clinical diagnostic applications.…”
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Clinical application and immune infiltration landscape of stemness‐related genes in heart failure by Wenting Yan, Yanling Li, Gang Wang, Yuan Huang, Ping Xie

“…Feature selection was performed using two machine learning algorithms. Nomogram models were then constructed to predict HF risk based on the selected key genes. …”
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Stochastic <i>H</i>_∞ Filtering of the Attitude Quaternion by Daniel Choukroun, Lotan Cooper, Nadav Berman

“…Thanks to the bilinear structure of the quaternion state-space model, the algorithm parameters are independent of the state. …”
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Cardiac Computed Tomography Measurements in Pulmonary Embolism Associated with Clinical Deterioration by Anthony J. Weekes, Angela M. Pikus, Parker L. Hambright, Kelly L. Goonan, Nathaniel O’Connell

“…Introduction: Most pulmonary embolism response teams (PERT) use a radiologist-determined right ventricle to left ventricle ratio (RV:LV) cut-off of 1.0 to risk-stratify pulmonary embolism (PE) patients. …”
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