Unraveling Spatial Heterogeneity in Mass Spectrometry Imaging Data with GraphMSI by Lei Guo, Peisi Xie, Xionghui Shen, Thomas Ka Yam Lam, Lingli Deng, Chengyi Xie, Xiangnan Xu, Chris Kong Chu Wong, Jingjing Xu, Jiacheng Fang, Xiaoxiao Wang, Zhuang Xiong, Shangyi Luo, Jianing Wang, Jiyang Dong, Zongwei Cai

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Deep Convolutional Neural Networks in Medical Image Analysis: A Review by Ibomoiye Domor Mienye, Theo G. Swart, George Obaido, Matt Jordan, Philip Ilono

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An Efficient Privacy-preserving Deep Learning Scheme for Medical Image Analysis by J. Andrew Onesimu, J Karthikeyan

“…In recent privacy has emerged as one of the major concerns of deep learning, since it requires huge amount of personal data. Medical Image Analysis is one of the prominent areas where sensitive data are shared to a third party service provider. …”
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Optimisation of Residual Network Using Data Augmentation and Ensemble Deep Learning for Butterfly Image Classification by Diniati Ruaika, Shofwatul Uyun

“…Convolutional Neural Networks (CNN) have proven effective for image analysis. …”
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Neural network as a mirror of social attitudes: analysis of distortions in generative images by A. G. Tertyshnikova, U. O. Pavlova, M. D. Starovoytova

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Image Reconstruction Algorithm Based on Tree Sparsity Model for Visual Sensor Network by Min Hu, Xuwei Huang, Dan Long, Cailiang Shen

“…A tree sparsity mode1 based image compressed sensing（CS）algorithm was proposed to efficiently explore the correlation in visua1 sensor networks（VSN）data. …”
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Comprehensive Review and Analysis of Image Encryption Techniques by K. Mahalakshmi, Sivakumar Nagarajan

“…The rapid growth of digital media has increased the need to protect image data from unauthorized access, particularly in fields such as medical imaging, military communication, and online content distribution. …”
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HyperKon: A Self-Supervised Contrastive Network for Hyperspectral Image Analysis by Daniel La’ah Ayuba, Jean-Yves Guillemaut, Belen Marti-Cardona, Oscar Mendez

“…However, RGB-based networks do not take full advantage of the spectral information in hyperspectral data. …”
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Motion correction in MR image for analysis of VSRAD using generative adversarial network. by Nobukiyo Yoshida, Hajime Kageyama, Hiroyuki Akai, Koichiro Yasaka, Haruto Sugawara, Yukinori Okada, Akira Kunimatsu

“…However, motion artifacts during acquisition of images may distort the results of the analysis. This study aims to evaluate the usefulness of the Pix2Pix network in motion correction for the input image of VSRAD analysis. …”
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Comprehensive analysis of supervised learning methods for electrical source imaging by Sarah Reynaud, Adrien Merlini, Douraied Ben Salem, François Rousseau

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Characterising the Thematic Content of Image Pixels with Topologically Structured Clustering by Giles M. Foody

“…The latter is central to an image classification analysis, notably as an input (e.g., training data for a supervised classifier) and/or an output (e.g., predicted class label). …”
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Transforming tabular data into images via enhanced spatial relationships for CNN processing by Hameedah A. Alenizy, Jawad Berri

“…Abstract Convolutional neural networks (CNNs), renowned for their efficiency in image analysis, have revolutionized pattern and structure recognition in visual data. …”
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Development of a Thermal Infrared Network for Volcanic and Environmental Monitoring: Hardware Design and Data Analysis Software Code by Fabio Sansivero, Giuseppe Vilardo, Ciro Buonocunto

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Cloud Removal in Full-disk Solar Images Using Deep Learning by Zhenhong Shang, Peng Du, Zhenping Qiang, Runxin Li

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Histopathological Image Analysis Using Deep Learning Framework by Sudha Rani Vupulluri, Jogendra Kumar Munagala

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Image data-driven intelligent recognition of permafrost strength and feature visualization based analysis by Zhaoming YAO, Xun WANG, Hang WEI, Xiaolong WANG

“…A convolutional neural network-based image data-driven intelligent recognition method for frozen soil strength is proposed. …”
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Deep Learning-Based In Situ Micrograph Synthesis and Augmentation for Crystallization Process Image Analysis by Muyang Li, Tuo Yao, Jian Liu, Ziyi Liu, Zhenguo Gao, Junbo Gong

“…Deep learning-based in situ imaging and analysis for crystallization process are essential for optimizing product qualities, reducing experimental costs through real-time monitoring, and controlling the process. …”
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Developments in Deep Learning Artificial Neural Network Techniques for Medical Image Analysis and Interpretation by Olamilekan Shobayo, Reza Saatchi

“…This article explores recent developments in deep learning techniques applied to medical imaging, including convolutional neural networks (CNNs) for classification and segmentation, recurrent neural networks (RNNs) for temporal analysis, autoencoders for feature extraction, and generative adversarial networks (GANs) for image synthesis and augmentation. …”
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Generative Adversarial Networks in Histological Image Segmentation: A Systematic Literature Review by Yanna Leidy Ketley Fernandes Cruz, Antonio Fhillipi Maciel Silva, Ewaldo Eder Carvalho Santana, Daniel G. Costa

“…The analyzed studies demonstrated the versatility of GANs in handling challenges like stain variability, multi-task segmentation, and data scarcity—all crucial challenges in the analysis of histopathological images. …”
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Application analysis of computer vision and image recognition based on improved VGG16 network by Xuanzhang Zhu, Yafei Li

“…On the basis of improving the deep convolutional neural network model, combined with the boundary Fisher analysis algorithm that can recognize high-dimensional data, an image recognition model is constructed to achieve efficient recognition of visual images. …”
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