Artificial neural networks in cardiology: analysis of graphic data by P. S. Onishchenko, K. Yu. Klyshnikov, E. A. Ovcharenko

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Spatial-Temporal Semantic Feature Interaction Network for Semantic Change Detection in Remote Sensing Images by Yuhang Zhang, Wuxia Zhang, Songtao Ding, Siyuan Wu, Xiaoqiang Lu

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Towards scalable medical image compression using hybrid model analysis by Shunlei Li, Jiajie Lu, Yingbai Hu, Leonardo S. Mattos, Zheng Li

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Machine Learning Model for Processing Aerospace Images of the Earthʼs Surface by T. F. Starovoitova, I. A. Starovoitov

“…A data processing model has been developed based on the Python programming language and neural networks, the purpose of which is to improve the recognition of objects in aerospace images. …”
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Coffee Beans Classification Using Convolutional Neural Networks Based On Extraction Value Analysis In Grayscale Color Space by Bagus Raffi Santoso, Christy Atika Sari, Eko Hari Rachmawanto

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Systematic review and network meta-analysis of retinal imaging biomarkers in neurodegenerative diseases: Correlation with brain changes by Farzaneh Nikparast, Zohreh Ganji, Hoda Zare, Nooshin Akbari-Sharak

“…Both undergo structural, vascular, and physiological changes in neurodegenerative diseases (NDs). This Systematic and network meta-analysis (NMA) aims to identify retinal-brain biomarkers across the spectrum of NDs. …”
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Fractal Neural Network Approach for Analyzing Satellite Images by Volodymyr Shymanskyi, Oleh Ratinskiy, Nataliya Shakhovska

“…Fractal neural networks offer a promising approach for automating satellite image analysis, providing better accuracy and robustness compared to traditional CNNs architectures.…”
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A Spatiotemporal Data Cube Approach to Classification of Variable Stars: A Catalog of Candidate Variable Stars from the TESS Full-frame Image Raw Data by Harry Qiang, Marina Kounkel, Sally Bass, Ryan Lingg, Logan Sizemore, Dylan Carroll, Brian Hutchinson, Keivan G. Stassun

“…We perform a search for eclipsing, pulsating, and rotating variables in TESS full-frame images. This classification was done using a neural network that has been trained on variable stars identified in other surveys. …”
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Wavelet-Based Topological Loss for Low-Light Image Denoising by Alexandra Malyugina, Nantheera Anantrasirichai, David Bull

“…Despite significant advances in image denoising, most algorithms rely on supervised learning, with their performance largely dependent on the quality and diversity of training data. …”
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Biomedical Data Annotation: An OCT Imaging Case Study by Matthew Anderson, Salman Sadiq, Muzammil Nahaboo Solim, Hannah Barker, David H. Steel, Maged Habib, Boguslaw Obara

“…Due to the quantity of data generated from OCT scans and the time taken for an ophthalmologist to inspect for various disease pathology features, automated image analysis in the form of deep neural networks has seen success for the classification and segmentation of OCT layers and quantification of features. …”
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CyclicAugment: Optimized Medical Image Analysis via Adaptive Augmentation Intensity by Min-Jun Kim, Jung-Woo Chae, Hyun-Chong Cho

“…Computer-aided diagnosis (CADx) systems play a crucial role in accurately diagnosing and monitoring diseases through medical imaging. However, there are many challenges, such as data scarcity and complex structural patterns, limiting the performance of deep-learning models. …”
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Automated analysis of high‐content microscopy data with deep learning by Oren Z Kraus, Ben T Grys, Jimmy Ba, Yolanda Chong, Brendan J Frey, Charles Boone, Brenda J Andrews

“…Here, we demonstrate that the application of deep learning to biological image data can overcome the pitfalls associated with conventional machine learning classifiers. …”
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Dynamic selectout and voting-based federated learning for enhanced medical image analysis by Saeed Iqbal, Adnan N Qureshi, Musaed Alhussein, Khursheed Aurangzeb, Atif Mahmood, Saaidal Razalli Bin Azzuhri

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Multistage Feature Complimentary Network for Single-Image Deraining by Kangying Wang, Minghui Wang

“…Finally, we use the effective information of the previous stage to guide the rain removal of the next stage by the recurrent neural network. The final experimental results show that a multistage feature complementarity network performs well on both synthetic rainy data sets and real-world rainy data sets can remove rain more completely, preserve more background details, and achieve better visual effects compared with some popular single-image deraining methods.…”
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Image Compression Based on Clustering Fuzzy Neural Network by Shahba Khaleel, Jamal Majeed, Bayda Khaleel

“…This has driven the research area of image compression to develop algorithm that compress images to lower data rates with better quality. …”
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Artistic features of neural networks: Image and video generation in the context of museum practice by Ivan V. Filippskiy

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A Patent Infringement Analysis Approach Based on Patent Knowledge Graph Driven Fusion of Graph and Image Similarity by Liting Jing, Chenlong Zhou, Di Feng, Yubo Dou, Xiaoyan Fan, Shaofei Jiang

“…Furthermore, the potential of patent images in infringement analysis remains underutilized. …”
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Triple-layered security system: reliable and secured image communications over 5G and beyond networks by Tarek Srour, Mohsen A. M. El-Bendary, Mostafa Eltokhy, Atef E. Abouelazm

“…This vision involves transferring a massive amount of data with very high levels of security. This paper presents the proposed vision of 5G and beyond security to build a research gap of existing and related technique that lack the adaptation, boosting gradient and complexity analysis, through design and evaluate the adapted and graded security system. …”
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Research on Park Perception and Understanding Methods Based on Multimodal Text–Image Data and Bidirectional Attention Mechanism by Kangen Chen, Xiuhong Lin, Tao Xia, Rushan Bai

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Assimilation of Moderate-Resolution Imaging Spectroradiometer Level Two Cloud Products for Typhoon Analysis and Prediction by Haomeng Zhang, Yubao Liu, Yu Qin, Zheng Xiang, Yueqin Shi, Zhaoyang Huo

“…A novel data assimilation technique is developed to assimilate MODIS (Moderate Resolution Imaging Spectroradiometer) level two (L2) cloud products, including cloud optical thickness (COT), cloud particle effective radius (Re), cloud water path (CWP), and cloud top pressure (CTP), into the Weather Research and Forecast (WRF) model. …”
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