Skin cancer detection using dermoscopic images with convolutional neural network by Khadija Nawaz, Atika Zanib, Iqra Shabir, Jianqiang Li, Yu Wang, Tariq Mahmood, Amjad Rehman

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Lithium-Ion Battery Health Assessment Method Based on Double Optimization Belief Rule Base with Interpretability by Zeyang Si, Jinting Shen, Wei He

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A Fault Identification Method for Electric Submersible Pumps Based on DAE-SVM by Peihao Yang, Jiarui Chen, Hairong Zhang, Sheng Li

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RLita: A Region-Level Image–Text Alignment Method for Remote Sensing Foundation Model by Qiang Zhang, Decheng Wang, Xiao Yu

“…Specifically, a region-level image–text alignment optimization method is proposed to represent the features of images and texts as visual and sematic representation vectors in one embedding space for better model generalization, and a parameter-efficient tuning strategy is designed to reduce computational resources. …”
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Data-driven insights into groundwater quality: machine and deep learning approaches by Gift Mbuzi, Abdur Rashid Sangi, Baha Ihnaini, Anil Carie, Sruthi Sivarajan, Satish Anamalamudi

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Effective Gait Abnormality Detection in Parkinson’s Patients for Multi-Sensors Surveillance System by Abdulwahab Alazeb, Mouazma Batool, Naif Al Mudawi, Mohammed S. Alshehri, Sultan Almakdi, Nouf Abdullah Almujally, Asaad Algarni

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Two-Stage Estimation for Ultrahigh Dimensional Sparse Quadratic Discriminant Analysis by Shengbin Zhou, Yejin Huang, Xiue Gao

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Information Security and Artificial Intelligence–Assisted Diagnosis in an Internet of Medical Thing System (IoMTS) by Pi-Yun Chen, Yu-Cheng Cheng, Zi-Heng Zhong, Feng-Zhou Zhang, Neng-Sheng Pai, Chien-Ming Li, Chia-Hung Lin

“…Recently, artificial intelligence (AI)- based methods are being increasingly applied to preprocess digital data and extract features. The key physiological parameters and feature patterns can then be incorporated into AI- based tools to help monitor, detect, and diagnose applications. …”
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Transmuted exponential-compound Weibull distribution for modelling of positively skewed data by Nnaemeka Martin Eze, Waheed Babatunde Yahya

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Explainable AI-Driven Quantum Deep Neural Network for Fault Location in DC Microgrids by Amir Hossein Poursaeed, Farhad Namdari

“…The model uses a combination of deep learning and quantum computing techniques to extract features and improve accuracy. …”
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A Recognition Method for Marigold Picking Points Based on the Lightweight SCS-YOLO-Seg Model by Baojian Ma, Zhenghao Wu, Yun Ge, Bangbang Chen, He Zhang, Hao Xia, Dongyun Wang

“…The approach enhances the baseline YOLOv8n-seg architecture by replacing its backbone with StarNet and introducing C2f-Star, a novel lightweight feature extraction module. These modifications achieve substantial model compression, significantly reducing the model size, parameter count, and computational complexity (GFLOPs). …”
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Sea Surface Height Inversion Model Based on Multimodal Deep Learning for the Fusion of Heterogeneous FY-3E GNSS-R Data by Yun Zhang, Ganyao Qin, Shuhu Yang, Yanling Han, Zhonghua Hong

“…Traditional physical altimetry methods based on delay–Doppler mapping (DDM) are subject to errors that are difficult to correct computationally. The current deep-learning-based SSH inversion techniques primarily relying on single-modal data are unable to fully leverage the rich feature information from global navigation satellite system reflectometry (GNSS-R) remote sensing data, therefore limiting the potential accuracy improvement. …”
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Vehicle Re-Identification Method Based on Efficient Self-Attention CNN-Transformer and Multi-Task Learning Optimization by Yu Wang, Rui Li, Yihan Shao

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Particle motion and QPOs around Euler-Heisenberg black hole immersed in cold dark matter halo by G. Mustafa, S.K. Maurya, Tayyab Naseer, Arzu Cilli, Ertan Güdekli, Assmaa Abd-Elmonem, Neissrien Alhubieshi

“…We explore the motion of particles in the vicinity of an Euler-Heisenberg black hole immersed in a cold dark matter halo, focusing on how the black hole parameters influence particle dynamics. This black hole solution is characterized by five parameters, namely, the black hole mass M, the feature radius R, the parameter ρ describing the density of the cold dark matter halo, the quantum electrodynamics parameter α, and the black hole charge Q. …”
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ADULT-ONSET STILL’S DISEASE: ASPECTS OF THE HEMATOLOGY CLINIC by M. M. Agakishiev, I. I. Mulina, A. M. Popova, I. N. Nechunaeva, L. M. Maslova, I. B. Kovynev, T. I. Pospelova

“…The relative value of positron emission computed tomography data, which can be falsely interpreted, is shown. …”
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Carreau’s Rheological Model and A.N. Tikhonov’s Regularization Method: Parametric Identification Based on a CFD model by Anatoly A. Khvostov, Gazibeg O. Magomedov, Victor I. Ryazhskih, Aleksey V. Kovalev, Aleksey A. Zhuravlev, Magomed G. Magomedov

“…Study objects and methods. The study featured fondant mass produced according to the traditional formulation for Creamy Fondant unglazed candies. …”
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Isogeometric analysis of the lithosphere under topographic loading: Igalith v1.0.0 by R. Rosandi, Y. Rosandi, B. Simeon

“…For Europe, the computed lithospheric depression is compared with available Mohorovičić depth data. …”
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Comprehensive Eye Diagram Analysis: A Transfer Learning Approach by Danshi Wang, Yilan Xu, Jianqiang Li, Min Zhang, Jin Li, Jun Qin, Cheng Ju, Zhiguo Zhang, Xue Chen

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GYS-RT-DETR: A Lightweight Citrus Disease Detection Model Based on Integrated Adaptive Pruning and Dynamic Knowledge Distillation by Linlin Yang, Zhonghao Huang, Yi Huangfu, Rui Liu, Xuerui Wang, Zhiwei Pan, Jie Shi

“…Secondly, the model adopts two model optimization strategies: (1) The Group_taylor local pruning algorithm is used to reduce memory occupation and the number of computing parameters of the model. (2) The feature-logic knowledge distillation framework is proposed and adopted to solve the problem of information loss caused by the structural difference between teachers and students, and to ensure a good detection performance, while realizing the lightweight character of the model. …”
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QAR Data Imputation Using Generative Adversarial Network with Self-Attention Mechanism by Jingqi Zhao, Chuitian Rong, Xin Dang, Huabo Sun

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