Application of deep learning model based on unenhanced chest CT for opportunistic screening of osteoporosis: a multicenter retrospective cohort study by Chengbin Huang, Dengying Wu, Bingzhang Wang, Chenxuan Hong, Jiasen Hu, Zijian Yan, Jianpeng Chen, Yaping Jin, Yingze Zhang

“…Key Points The application of unenhanced chest CT is increasing. Most people do not consciously use DXA to screen themselves for osteoporosis. …”
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Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…Objective Combining an inertial navigation system (INS) and a global positioning system (GPS) in stable conditions of GPS satellite signals offers the most accurate altitude indication, termed inertial satellite composite altitude. …”
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Deep Learning-Based Fake-Banknote Detection for the Visually Impaired People Using Visible-Light Images Captured by Smartphone Cameras by Tuyen Danh Pham, Chanhum Park, Dat Tien Nguyen, Ganbayar Batchuluun, Kang Ryoung Park

“…Research on this task has mostly involved methods applied to automatic sorting machines with multiple imaging sensors or that use specialized sensors for capturing banknote images in various light wavelengths. …”
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A Comparative Study of Image Processing and Machine Learning Methods for Classification of Rail Welding Defects by Mohale Emmanuel Molefe, Jules Raymond Tapamo, Siboniso Sithembiso Vilakazi

“…Defects formed during the thermite welding process of two sections of rails require the welded joints to be inspected for quality, and the most used non-destructive method for inspection is radiography testing. …”
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Field-grown tomato yield estimation using point cloud segmentation with 3D shaping and RGB pictures from a field robot and digital single lens reflex cameras by B. Ambrus, G. Teschner, A.J. Kovács, M. Neményi, L. Helyes, Z. Pék, S. Takács, T. Alahmad, A. Nyéki

“…The best fitting sphere model was generated using the 3D model. The most optimal model was the 3D model, which gave the best representation and provided the weight of the tomatoes with a relative error of 21.90 % and a standard deviation of 17.9665 %. …”
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A Novel Local Binary Patterns-Based Approach and Proposed CNN Model to Diagnose Breast Cancer by Analyzing Histopathology Images by Mehmet Gul

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A Study of Deep Learning Models for Audio Classification of Infant Crying in a Baby Monitoring System by Denisa Maria Herlea, Bogdan Iancu, Eugen-Richard Ardelean

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Real-Time Pipeline Leak Detection: A Hybrid Deep Learning Approach Using Acoustic Emission Signals by Faisal Saleem, Zahoor Ahmad, Jong-Myon Kim

“…A genetic algorithm (GA) optimizes the neural network by isolating the most important features for leak detection. The final classification stage uses a fully connected neural network to categorize pipeline health conditions as either ‘leak’ or ‘non-leak’. …”
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Effective classification of android malware families through dynamic features and neural networks by Gianni D'Angelo, Francesco Palmieri, Antonio Robustelli, Arcangelo Castiglione

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An Overview of CNN-Based Image Analysis in Solar Cells, Photovoltaic Modules, and Power Plants by Dávid Matusz-Kalász, István Bodnár, Marcell Jobbágy

“…We aimed to summarize the most recent articles for 2024 and 2025. The annual volume of solar panels produced is expected to increase in the future. …”
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Transfer Learning for Cancer Diagnosis in Medical Images: A Compendious Study by Navreet Kaur, Rahul Hans

“…Abstract In today’s world, cancer stands out as one of the most perilous diseases, caused by the uncontrolled proliferation of cells within the human body. …”
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Alzheimer’s disease diagnosis by 3D-SEConvNeXt by Zhongyi Hu, Yuhang Wang, Lei Xiao

“…Abstract Alzheimer’s disease (AD) constitutes a fatal neurodegenerative disorder and represents the most prevalent form of dementia among the elderly population. …”
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Deep Learning Neurons in Medical Insight: Revolutionizing Image Analysis for Disease Prediction and Diagnosis by Moise Hermann Mabouh

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Enhanced melanoma and non-melanoma skin cancer classification using a hybrid LSTM-CNN model by Sara M. M. Abohashish, Hanan H. Amin, E. I. Elsedimy

“…Abstract Melanoma is the most dangerous type of skin cancer. Although it accounts for only about 1% of all skin cancer cases, it is responsible for the majority of skin cancer-related deaths. …”
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DETERMINATION OF THE BEST OPTIMIZER FOR A NEURONETWORK IN THE DEVELOPMENT OF AUTOMATIC IMAGE TAGGING SYSTEMS by Andrian Kozynets

“…Comparing these optimizers allows us to determine the most suitable optimizer for solving specific machine learning problems. …”
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Hybrid CNN-Transformer Architecture With Xception-Based Feature Enhancement for Accurate Breast Cancer Classification by Alireza Zeynali, Mohammad Ali Tinati, Behzad Mozaffari Tazehkand

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Towards Optimizing Neural Network-Based Quantification for NMR Metabolomics by Hayden Johnson, Aaryani Tipirneni-Sajja

“…<b>Results:</b> The transformer was the most effective network for NMR metabolite quantification, especially as the number of metabolites per spectra increased or target concentrations were low or had a large dynamic range. …”
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A hybrid deep learning model for predicting atmospheric corrosion in steel energy structures under maritime conditions based on time-series data by Mohamed El Amine Seghier Ben, Tam T. Truong, Christian Feiler, Daniel Höche

“…Atmospheric corrosion of maritime structures remains one of the most challenging issues facing offshore industry. …”
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Predicting Wealth Score from Remote Sensing Satellite Images and Household Survey Data Using Deep Learning by Shashank Shekhar, Pratibha Singh, Rashmi Mishra, Sunil Kumar

“… The most exigent call of the United Nations’ 17 sustainable goals is to end poverty everywhere by 2030. …”
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An enhanced deep learning model for accurate classification of ovarian cancer from histopathological images by Anik Kumar Saha, Muntezar Rabbani, Anika Saba Ibte Sum, M. F. Mridha, Md Mohsin Kabir

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