Wavelet-Based Topological Loss for Low-Light Image Denoising by Alexandra Malyugina, Nantheera Anantrasirichai, David Bull

“…However, the analysis of real-world data suggests that this assumption is invalid. …”
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CDBA-GAN: A Conditional Dual-Branch Attention Generative Adversarial Network for Robust Sonar Image Generation by Wanzeng Kong, Han Yang, Mingyang Jia, Zhe Chen

“…Consequently, sonar image simulation technology has become increasingly vital in the field of sonar data analysis. …”
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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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Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging by Chiara Manini, Markus Hüllebrand, Lars Walczak, Sarah Nordmeyer, Lina Jarmatz, Titus Kuehne, Heiko Stern, Christian Meierhofer, Andreas Harloff, Jennifer Erley, Sebastian Kelle, Peter Bannas, Ralf Felix Trauzeddel, Jeanette Schulz-Menger, Anja Hennemuth

“…ABSTRACT: Background: Four-dimensional cardiovascular magnetic resonance flow imaging (4D flow CMR) plays an important role in assessing cardiovascular diseases. …”
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Sentiment Analysis from Face Expressions Based on Image Processing Using Deep Learning Methods by Orhan Emre Aksoy, Selda Güney

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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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MCFTNet: Multimodal Cross-Layer Fusion Transformer Network for Hyperspectral and LiDAR Data Classification by Wei Huang, Tianren Wu, Xueyu Zhang, Liangliang Li, Ming Lv, Zhenhong Jia, Xiaobin Zhao, Hongbing Ma, Gemine Vivone

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Deep learning for COVID-19 by X-ray images Analysis and Designing Diagnostic Application by Thamer Khaleel, Ali Kalakech

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Comparative Analysis of Deep Learning Methods for Classification of Ablated Regions in Hyperspectral Images of Atrial Tissue by Yeva Gabrielyan, Arpi Hunanyan, Sona Bezirganyan, Lusine Davtyan, Ani Avetisyan, Narine Sarvazyan, Aram Butavyan, Varduhi Yeghiazaryan

“…For both porcine and bovine data, models incorporating graph neural networks demonstrate superior performance. …”
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Enhancing Recognition and Categorization of Skin Lesions with Tailored Deep Convolutional Networks and Robust Data Augmentation Techniques by Syed Ibrar Hussain, Elena Toscano

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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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Active Contours Connected Component Analysis Segmentation Method of Cancerous Lesions in Unsupervised Breast Histology Images by Vincent Majanga, Ernest Mnkandla, Zenghui Wang, Donatien Koulla Moulla

“…Once all binary-masked groups have been determined, a deep-learning recurrent neural network (RNN) model from the Keras architecture uses this information to automatically segment nuclei objects having cancerous lesions on the image via the active contours method. …”
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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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ONLINE FUZZY CLUSTERING OF HIGH DIMENSION DATA STREAMS BASED ON NEURAL NETWORK ENSEMBLES by Yevgeniy Bodyanskiy, Iryna Perova, Polina Zhernova

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Dataset Dependency in CNN-Based Copy-Move Forgery Detection: A Multi-Dataset Comparative Analysis by Potito Valle Dell’Olmo, Oleksandr Kuznetsov, Emanuele Frontoni, Marco Arnesano, Christian Napoli, Cristian Randieri

“…Convolutional neural networks (CNNs) have established themselves over time as a fundamental tool in the field of copy-move forgery detection due to their ability to effectively identify and analyze manipulated images. …”
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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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DPA-HairNet: A Dual Encoder Attention Based Network for Hair Artifact Removal in Dermoscopic Images by F M Javed Mehedi Shamrat, Mohd Yamani Idna Idris, Chowdhury Forhadul Karim, Xujuan Zhou, Raj Gururajan

“…These results underscore DPA-HairNet’s effectiveness and potential integration into clinical workflows to enhance dermoscopic image analysis and diagnosis. Future work will explore generalization to additional artifact types and optimization for real-time clinical deployment.…”
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Enhancing Ground Penetrating Radar (GPR) Data Analysis Utilizing Machine Learning by Mohanad Shehab, Musab T.S. Al-Kaltakchi, Ammar Dukhan, Wai Lok Woo

“…Finally, various machine learning techniques are employed to classify the collected images using models like Decision Trees,agged trees, Naive Bayes, Artificial Neural Networks, Quadratic Discriminant Analysis, Support Vector Machines, and K-nearest neighbors. …”
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Soil Organic Matter Content Prediction Using Multi-Input Convolutional Neural Network Based on Multi-Source Information Fusion by Li Guo, Qin Gao, Mengyi Zhang, Panting Cheng, Peng He, Lujun Li, Dong Ding, Changcheng Liu, Francis Collins Muga, Masroor Kamal, Jiangtao Qi

“…This study proposes a novel approach to predict SOM content by integrating spectral, texture, and color features using a three-branch convolutional neural network (3B-CNN). Spectral reflectance data (400–1000 nm) were collected using a portable hyperspectral imaging device. …”
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GGLA-NeXtE2NET: A Dual-Branch Ensemble Network With Gated Global-Local Attention for Enhanced Brain Tumor Recognition by Adnan Saeed, Khurram Shehzad, Shahzad Sarwar Bhatti, Saim Ahmed, Ahmad Taher Azar

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