Harnessing artificial intelligence for predicting breast cancer recurrence: a systematic review of clinical and imaging data by Jaqueline Alvarenga Silveira, Alexandre Ray da Silva, Mariana Zuliani Theodoro de Lima

“…SVMs are effective with high-dimensional clinical data, while Neural Networks in genetic and molecular analysis. …”
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TransTab: A transformer-based approach for table detection and tabular data extraction from scanned document images by Yongzhou Wang, Wenliang Lv, Weijie Wu, Guanheng Xie, BiBo Lu, ChunYang Wang, Chao Zhan, Baishun Su

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Topological Data Analysis and Graph-Based Learning for Multimodal Recommendation by Khalil Bachiri, Ali Yahyaouy, Maria Malek, Nicoleta Rogovschi

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Generative Artificial Intelligence for Hyperspectral Sensor Data: A Review by Diaa Addeen Abuhani, Imran Zualkernan, Raghad Aldamani, Mohamed Alshafai

“…Airborne platforms and satellites provide rich sensor data in the form of hyperspectral images (HSI), which are crucial for numerous vision-related tasks, such as feature extraction, image enhancement, and data synthesis. …”
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Attention Deficit Hyperactivity Disorder identification: FMRI data analyzed with CNN and seed-based approach by Anika Siamin Oyshi, Mohammad Hasan, Md. Khabir Uddin Ahamed, Md. Sydur Rahman, Md. Mahfuzul Haque, Mahmudul Alam

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Synthetic Micrographs of Bacteria (SyMBac) allows accurate segmentation of bacterial cells using deep neural networks by Georgeos Hardo, Maximilian Noka, Somenath Bakshi

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The Image of City as Seen through Social Media Photographs: A Case Study of the Historical Context of Tabriz by Mahsa Chizfahm Daneshmandian, Morteza Mirgholami, Abbas Ghafari, Yaser Shahbazi

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End-to-End Stroke Imaging Analysis Using Effective Connectivity and Interpretable Artificial Intelligence by Wojciech Ciezobka, Joan Falco-Roget, Cemal Koba, Alessandro Crimi

“…In this paper, we propose a reservoir computing-based and directed graph analysis pipeline. The goal of this pipeline is to define an efficient brain representation for connectivity in stroke data derived from magnetic resonance imaging. …”
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A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images by Mishmala Sushith, A. Sathiya, V. Kalaipoonguzhali, V. Sathya

“…This paper presents a novel hybrid deep learning framework that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for diabetic retinopathy (DR) early detection and progression monitoring using retinal fundus images. …”
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Best practices for AI-based image analysis applications in aquatic sciences: The iMagine case study by Elnaz Azmi, Khadijeh Alibabaei, Valentin Kozlov, Tjerk Krijger, Gabriele Accarino, Sakina-Dorothée Ayata, Amanda Calatrava, Marco Mariano De Carlo, Wout Decrop, Donatello Elia, Sandro Luigi Fiore, Marco Francescangeli, Jean-Olivier Irisson, Rune Lagaisse, Martin Laviale, Antoine Lebeaud, Carolin Leluschko, Enoc Martínez, Germán Moltó, Igor Ruiz Atake, Antonio Augusto Sepp Neves, Damian Smyth, Jesús Soriano-González, Muhammad Arabi Tayyab, Vanessa Tosello, Álvaro López García, Dick Schaap, Gergely Sipos

“…One of the objectives of this project is to provide an AI platform that leverages AI-powered tools to improve the processing and analysis of imaging data from marine and freshwater ecosystems, contributing to the study of the health of oceans, seas, coasts, and inland waters. …”
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Estimation of Sediment Grain Size Distribution Using Optical Image-Based Spatial Feature Representation Learning with Data Augmentation by Jongwon Choi, Sulki Kim, Jaejoong Jin, Jinhoon Kim, Sungyeol Chang, Inho Kim

“…The proposed model was applied to 41 littoral systems located along the eastern coast of the Korean Peninsula and was developed using grain size distribution data through sieve analysis and images obtained from 2010 to 2024. …”
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Digital Mapping of Soil Equivalent Calcium Carbonate Using Landsat 8 Satellite Images and Environmental Data by Machine Learning Models in Badr Watershed, Kurdistan Province by M. Zarinibahador

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A generative benchmark for evaluating the performance of fluorescent cell image segmentation by Jun Tang, Wei Du, Zhanpeng Shu, Zhixing Cao

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Urban Environment and Momentary Psychological States: A Micro-Scale Study on a University Campus with Network Analysis by Fanxi Wang, Feng Qi

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Copper Stress Levels Classification in Oilseed Rape Using Deep Residual Networks and Hyperspectral False-Color Images by Yifei Peng, Jun Sun, Zhentao Cai, Lei Shi, Xiaohong Wu, Chunxia Dai, Yubin Xie

“…For spatial image data, deep residual networks were employed to evaluate the effectiveness of visible-light and false-color images. …”
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Analysis of space solar array arc images based on deep learning techniques by Afaf M. Abd El-Hameed, Ahmed S. Farahat, Khaled Y. Youssef, M. Elfarran, I. M. Selim

“…The presented study aims to investigate discharging and arc spectra on solar cell surfaces through the analysis of arc images. Leveraging advanced Deep Learning (DL) methodologies, including Convolutional Neural Networks (CNN) and Transfer Learning, a robust predictive model has been developed to analyze arc behavior and identify defective cells based on image data. …”
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Integrating Fractional-Order Hopfield Neural Network with Differentiated Encryption: Achieving High-Performance Privacy Protection for Medical Images by Wei Feng, Keyuan Zhang, Jing Zhang, Xiangyu Zhao, Yao Chen, Bo Cai, Zhengguo Zhu, Heping Wen, Conghuan Ye

“…Compared with recent leading counterparts, MIES-FHNN-DE better meets the privacy protection demands for medical images in emerging fields like medical intelligent analysis and medical cloud services.…”
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Advanced deep learning models based on neutrosophic logic for the analysis of brain tumor medical images by Dina Atef, Doaa El Shaha

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Longitudinal whole-brain analysis of multi-subject diffusion data in diffuse axonal injury by Daphine Centola Grassi, Ana Luiza Zaninotto, Fabrício Stewan Feltrin, Fabíola Bezerra de Carvalho Macruz, Maria Concepción García Otaduy, Claudia da Costa Leite, Vinicius Monteiro de Paula Guirado, Wellingson Silva Paiva, Celi Santos Andrade

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Algorithm of Encrypting Digital Image Using Chaos Neural Network by Ying Mao

“…With the rapid development of digital communication technology, data and image encryption methods will get more and more in-depth research in these aspects. …”
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