Segmentation Techniques Applied to CNNs for Cervical Cancer Classification by Ana Ortiz-Gonzalez, Raquel Martinez-Espana, Juan Morales-Garcia, Baldomero Imbernon, Jose Martinez-Mas, Mauricio A. Alvarez, Oscar David Romero, Juan Pedro Martinez-Cendan, Andres Bueno-Crespo

“…In this paper, we design an automatic segmentation masks for the classification of cervicovaginal cell images. This automatic segmentation is combined in a classification model that allows the models to improve their performance thanks to the morphological information provided by the combined segmentation in a Global Average Pooling layer with the convolutional network analysis of the original image. …”
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Quantitative Analysis of Vertical and Temporal Variations in the Chlorophyll Content of Winter Wheat Leaves via Proximal Multispectral Remote Sensing and Deep Transfer Learning by Changsai Zhang, Yuan Yi, Shuxia Zhang, Pei Li

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Identification and evaluation of plasma exosome RNA biomarkers for non-invasive diagnosis of hepatocellular carcinoma using RNA-seq by Heqing Huang, Min Zhang, Hong Lu, Yiling Chen, Weijie Sun, Jinghan Zhu, Zutao Chen

“…The hub genes for HCC diagnosis were identified combining pathway enrichment analysis and protein–protein interaction network analysis. …”
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An artificial intelligence and machine learning-driven CFD simulation for optimizing thermal performance of blood-integrated ternary nano-fluid by Mohib Hussain, Du Lin, Hassan Waqas, Qasem M. Al-Mdallal

“…Regression scores equal to 1 indicate a good match between the actual data and the predictions. Conclusively, the proposed investigation provides insightful AI, ML and CFD-proposed analysis of blood-based nano-particles which can improve imaging techniques, provide tailored drug delivery, reduce hyperthermia, improve blood flow, and show potential for application in medicine.Highlights Artificial intelligence and machine learning-based CFD simulation of the blood-mediated tri-hybrid nano-fluid flow is presented.An improved finite difference scheme (the Keller-Box method), is utilized to numerically evaluate the problem.The LMA-ANN forecasts with an absolute error range of [Formula: see text] to [Formula: see text] relative to the actual data.Regression scores equal to 1 indicate a strong correlation between forecasts and actual data.…”
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Optimizing rural waste management: Leveraging high-resolution remote sensing and GIS for efficient collection and routing by Xi Cheng, Jieyu Yang, Zhiyong Han, Guozhong Shi, Deng Pan, Likang Meng, Zhuojun Zeng, Zhanfeng Shen

“…Within these clusters, an assortment of spatial regulations and evaluations facilitated the judicious selection of environmentally-conscious waste collection sites (WCSs). The Pointer Network, augmented with reinforcement learning, executed a traveling salesman analysis on these chosen WCSs, yielding the optimal collection trajectory. …”
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Fault diagnosis and inference of hoist main bearing based on transfer learning and ontology by Fei DONG, Di ZHANG, Kunpeng GE, Junjie CHEN, Xinyue XU

“…To overcome the challenges still faced by data-driven hoist main bearing fault diagnosis methods, including data imbalance due to a lack of fault samples under real operating conditions, diagnostic performance degradation of fault diagnosis models caused by significant differences in data sample distribution under varying conditions, single fault diagnosis function, and a lack of reasoning analysis and localization for the causes of hoist main bearing system failures, a new fault diagnosis and reasoning method for hoist main bearing systems is studied, which includes two aspects: ① Bearing fault diagnosis based on convolutional neural network transfer learning and domain adaptation. …”
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Redefining failure detection in PV Systems: a comparative study of GPT-4o and ResNet's computer vision in aerial infrared imagery analysis by Gallmetzer Sandra, Sondoqah Mousa, Turri Evelyn, Koester Lukas, Louwen Atse, Moser David

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Layer-by-Layer Multifractal Scanning of Optically Anisotropic Architectonics of Blood Plasma Films: Fundamental and Applied Aspects by Alexander Ushenko, Natalia Pavlyukovich, Oksana Khukhlina, Olexander Pavlyukovich, Mykhaylo Gorsky, Iryna Soltys, Alexander Dubolazov, Yurii Ushenko, Olexander Salega, Ivan Mikirin, Jun Zheng, Zhebo Chen, Lin Bin

“…Jones-matrix images of supramolecular networks, along with their corresponding theziograms of linear and circular birefringence, were obtained for each phase plane. …”
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A Deep-Learning Workflow for CORONA-Based Historical Land Use Classifications by Wei Liu, Shuai Li, Di Fan, Yixin Wen, Austin Madson, Jessica Mitchell, Yaqian He, Di Yang

“…Historical satellite imagery lacks efficient methods for automated land use mapping, particularly when working with CORONA satellite data from the Cold War era. These high-resolution images from the 1960s offer valuable insights into historic land use conditions, but require intensive preprocessing and lack standardized methods for analysis. …”
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A global overview of the use of cone beam computed tomography in dentistry: a bibliometric review focusing on paediatric patients [version 2; peer review: 2 approved] by Gabriela Beatriz Rigo Wietzkoski, Mariane Cardoso, Carla Miranda Santana, Julia Maldonado Garcia, Michely Cristina Goebel, Isabela Ramos, Pablo Silveira Santos, Lucas Menezes dos Anjos, Aurélio de Oliveira Rocha, Danielle Cristina Alves Rigo

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Innovations in Sensor-Based Systems and Sustainable Energy Solutions for Smart Agriculture: A Review by Md. Mahadi Hasan Sajib, Abu Sadat Md. Sayem

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Prototypical Few-Shot Learning for Histopathology Classification: Leveraging Foundation Models With Adapter Architectures by Kazi Rakib Hasan, Sijin Kim, Junghwan Cho, Hyung Soo Han

“…Histopathology is a critical tool for disease diagnosis and identifying cancer via microscopic tissue analysis. Traditional deep learning methods for histopathology often require extensive labeled data, which can be scarce and expensive. …”
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Harnessing YOLOv11 for Enhanced Detection of Typical Autism Spectrum Disorder Behaviors Through Body Movements by Ayman Noor, Hanan Almukhalfi, Arthur Souza, Talal H. Noor

“…<b>Methods</b>: The system’s multi-layered design integrates monitoring, network, cloud, and typical ASD behavior detection layers to facilitate real-time video acquisition, wireless data transfer, and cloud analysis along with ASD-typical behavior classification. …”
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Steering-Angle Prediction and Controller Design Based on Improved YOLOv5 for Steering-by-Wire System by Cunliang Ye, Yunlong Wang, Yongfu Wang, Yan Liu

“…Firstly, given that most lane-line data sets consist of simulated images and lack diversity, a novel lane data set derived from real roads is manually created to train the proposed network model. …”
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SympCoughNet: symptom assisted audio-based COVID-19 detection by Yuhao Lin, Xiu Weng, Bolun Zheng, Weiwei Zhang, Zhanjun Bu, Yu Zhou

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Site Suitability Analysis for Future Urban Development Using Analytic Hierarchy Process (AHP) Model: A Case Study in Hisar City, Haryana (India) by Sharma Manju, Kumar Vipin

“…The LISS-IV satellite image from October 17, 2022, was used to create a land use/land cover map for future urban development in Hisar City and its fringe area. …”
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Enhanced Emotion-Aware Conversational Agent: Analyzing User Behavioral Status for Tailored Reponses in Chatbot Interactions by S. Abinaya, K. S. Ashwin, A. Sherly Alphonse

“…This processed image is analyzed by a Convolutional Neural Network (CNN) model trained specifically for emotion recognition, reaching 74.14% accuracy by assigning probabilities to different emotions. …”
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Longitudinal structural MRI-based deep learning and radiomics features for predicting Alzheimer’s disease progression by Sepehr Aghajanian, Fateme Mohammadifard, Ida Mohammadi, Shahryar Rajai Firouzabadi, Ali Baradaran Bagheri, Elham Moases Ghaffary, Omid Mirmosayyeb

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A bird song detector for improving bird identification through deep learning: A case study from Doñana by Alba Márquez-Rodríguez, Miguel Ángel Mohedano-Munoz, Manuel J. Marín-Jiménez, Eduardo Santamaría-García, Giulia Bastianelli, Pedro Jordano, Irene Mendoza

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Scale-Free Dynamics of Resting-State fMRI Microstates by Nurhan Erbil, Gopikrishna Deshpande

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