Sea Surface Temperature Prediction Based on Spatio-Temporal Graph Contrastive Learning Network by Weihan Dai, Xiaoyu He, Xiulin Geng, Shuai Zhang, Ziheng Gao

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A Detection Method of Lentinus Edodes Based on Improved YOLOv4 Algorithm by HUANG Ying-lai, LI Da-ming, LU Xin, YANG Liu-song

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A Novel Quadrilateral Contour Disentangled Algorithm for Industrial Instrument Reading Detection by Xiang Li, Changchang Zeng, Yong Yao, Jide Qian, Haiding Zhang, Sen Zhang, Suixian Yang

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First-principles calculations on Ti2AlB2, Ti3AlB4 and Ti4AlB6, three potential new members of the orthorhombic MAB phase by Chen Tang, Lei Dong, Shihui Feng, Bowen Han, Mengying Liu, Zhaowei Liu, Yufei Tang, Kang Zhao

“…In this study, three potential Ti-based MABs (Ti2AlB2, Ti3AlB4 and Ti4AlB6) are predicted via first-principles calculations and density functional theory (DFT). The computational analyses confirm the thermodynamic and mechanical stability of these phases, with their lattice parameters determined, providing valuable references for future experimental endeavors. …”
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L-ENet: An Ultralightweight SAR Image Detection Network by Yutong Wang, Min Miao, Shiliang Zhu

“…Experimental results show that L-ENet has a computational cost of 0.6 M and a parameter count of 2.1 giga floating point operations per second. …”
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An improved DeepLabv3 + railway track extraction algorithm based on densely connected and attention mechanisms by Yanbin Weng, Jie Yang, Changfan Zhang, Jing He, Cheng Peng, Lin Jia, Hui Xiang

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SHIFA: SBERT-Based Healthcare Information Focused Arabic Question Answering by Rahaf Alruwaithi, Sarah AlHumoud

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Demystifying DFT-Based Harmonic Phase Estimation, Transformation, and Synthesis by Marco Oliveira, Vasco Santos, André Saraiva, Aníbal Ferreira

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Empowering sentiment analysis in social media: a comprehensive approach to enhance the classification of abusive Tamil comments using transformer models by Malliga Subramanian, Sathishkumar Veerappampalayam Easwaramoorthy, Nandhini Subbarayan, Usha Moorthy

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A lightweight real-time unified detection model for rice and wheat ears in complex agricultural environments by Xiaojun Shen, Shuai Li, Fen Qiu, Lili Yao

“…The model utilizes the lightweight MobileNetV3 network combined with the dynamic detection head DyHead to reconstruct the YOLOv5s network. Through multi-scale feature aggregation and attention mechanisms, the model effectively enhances its ability to capture dense targets in complex scenarios while reducing computational redundancy. …”
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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

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Physical Information Neural Network-Based Seepage Behavior Analysis of Earth and Rock Dams by XUE binghan, HUANG zhenhua, LEI Jianwei, FANG Hongyuan

“…This substantially enhances computational efficiency.…”
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Reliability of radiomic analysis on multiparametric MRI for patients affected by autosomal dominant polycystic kidney disease by Francesca Lussana, Ettore Lanzarone, Giulia Villa, Alfonso Mastropietro, Anna Caroli, Elisa Scalco

“…Additionally, lower-order features, including those computed from histograms and co-occurrence matrices, demonstrate higher reproducibility than other texture features.…”
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Open-source Flux Transport (OFT). I. HipFT–High-performance Flux Transport by Ronald M. Caplan, Miko M. Stulajter, Jon A. Linker, Cooper Downs, Lisa A. Upton, Bibhuti Kumar Jha, Raphael Attie, Charles N. Arge, Carl J. Henney

“…The Open-source Flux Transport (OFT) model seeks to fill this gap by providing an open and user-extensible SFT model that also builds on the knowledge of previous models with updated numerical and data acquisition/assimilation methods along with additional user-defined features. In this first of a series of papers on OFT, we introduce its computational core: the High-performance Flux Transport (HipFT) code ( https://github.com/predsci/hipft ). …”
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Optimizing deep learning models to combat amyotrophic lateral sclerosis (ALS) disease progression by Haoshen Qin, Lal Hussain, Ziang Liu, Xu Yan, Fuad A. Awwad, Faisal Mehmood Butt, Umair Ahmad Salaria, Emad A.A. Ismail

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Detection algorithm for wearing safety helmet under mine based on improved YOLOv5s by Yuanbin WANG, Sixiong WEI, Huaying WU, Yu DUAN, Meng LIU

“…Aiming at the problems of low accuracy and high missed detection rate of personnel safety helmet detection algorithm caused by complex environment under mine, an improved mine safety helmet detection algorithm based on YOLOv5s is proposed. Due to the computer system, the global context information of the image is easily lost when the convolutional neural network extracts the features, resulting in poor detection effect of the downhole small target safety helmet. …”
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An interpretable machine learning model for predicting bone marrow invasion in patients with lymphoma via 18F-FDG PET/CT: a multicenter study by Xinyu Zhu, Denglu Lu, Yang Wu, Yanqi Lu, Liang He, Yanyun Deng, Xingyu Mu, Wei Fu

“…We aimed to develop and validate an interpretable machine learning model that integrates clinical data, 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) parameters, radiomic features, and deep learning features to predict BMI in lymphoma patients. …”
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Lightweight grading segmentation network for powdery mildew based on model pruning and knowledge distillation by Yuheng Li, Lisha Ye, Yu Zhang, Lijuan Zhou, Qian Chen

“…Our contributions are fourfold: First, we establish a high-performance baseline, PMSeg, which integrates a Mixed Aggregation Network (MANet) and a Channel-wise Cross Fusion Transformer (CCFT) to significantly enhance sensitivity to small targets and multi-scale feature extraction. Second, to achieve on-device feasibility, we systematically compress PMSeg into light-PMSeg through a novel combination of slimming pruning and knowledge distillation (KD), which restores performance after parameter reduction. …”
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A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification by Manishi Shakya, Ravindra Patel, Sunil Joshi

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Fault Diagnosis of Electric Impact Drills Based on Time-Varying Loudness and Logistic Regression by Yapeng Jing, Haitao Su, Shao Wang, Wenhua Gui, Qing Guo

“…A feature extraction peak-to-average ratio (PAR) method based on the time-varying loudness spectrum was described and implemented to compute the feature vectors. …”
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