Study of Recent Image Restoration Techniques: A Comprehensive Survey by Nikita Singhal, Anup Kadam, Pravesh Kumar, Hritik Singh, Aaryan Thakur, Pranay

“…Restoration is important in many applications, including medical imaging, surveillance, photography, and remote sensing, where image quality will be critical to the correctness of analysis and decision. …”
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ANALYSIS OF EMOTION RECOGNITION BASED ON DEEP CONVOLUTIONAL NEURAL NETWORK MODELS by V. M. Goryaev, G. A. Mankaeva, T. B. Ochir-Goryaeva, A. B. Mantusov, V. V. Lidji-Garyaev, A. B. Kornyakov

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White matter and cortical gray matter microstructural alterations in migraine: a NODDI and DTI analysis by Zhilei Li, Yanliang Mei, Lei Wang, Tianhua Fan, Cheng Peng, Kaibo Zhang, Shouyi Wu, Tong Chen, Zhenchang Zhang, Binbin Sui, Yonggang Wang, Xueying Yu

“…Methods Microstructural alterations in both white matter (WM) and cortical gray matter (GM) were evaluated among 40 chronic migraine (CM) patients, 35 episodic migraine (EM) patients, and 45 healthy controls (HCs) using Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI) models. …”
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Multi‐sensor missile‐borne LiDAR point cloud data augmentation based on Monte Carlo distortion simulation by Luda Zhao, Yihua Hu, Fei Han, Zhenglei Dou, Shanshan Li, Yan Zhang, Qilong Wu

“…However, due to the complex and distinct characteristics of LiDAR point cloud data from different platforms (such as missile‐borne and vehicular LiDAR data), directly applying traditional 2D visual domain DA methods to 3D data can lead to networks trained using this approach not robustly achieving the corresponding tasks. …”
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Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction by Amun Jarzembski, Siddharth Nair, Wyatt Hodges, Matthew Jordan, Anthony McDonald, Logan Antiporda, Greg W. Pickrell, Timothy Walsh, Fabio Semperlotti, Jason Neely, Luke Yates

“…Taken together, FDTR with neural network‐based analysis demonstrates subsurface bond monitoring at length scales relevant for heterogeneously integrated microelectronics.…”
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Natural soils’ shear strength prediction: A morphological data-centric approach by Maher Omar, Mohamed G. Arab, Emran Alotaibi, Khalid A. Alshibli, Abdallah Shanableh, Hussein Elmehdi, Dima A. Hussien Malkawi, Ali Tahmaz

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DeepGray: Malware Classification Using Grayscale Images with Deep Learning by Haodi Jiang, Harshitha Polsani, Yuexin Liu

“…The methodology involves transforming executable files into a deep learning-friendly format by converting them into grayscale images while preserving essential data characteristics. …”
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Automated detection of submarine pipelines in the Yellow River Estuary: a deep learning approach for side-scan sonar data in dynamic deltaic systems by Min Wei, Min Wei, Yongqing Yu, Xing Du, Yupeng Song, Lifeng Dong, Qikun Zhou, Linfeng Wang, Longying Zhang, Yamei Wang

“…Conversely, VGG-16 shows comparatively weaker performance, making it less suitable for SSS image analysis. Notably, data expansion significantly influences model accuracy, although its impact varies across different models. …”
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A novel diagnostic framework for breast cancer: Combining deep learning with mammogram-DBT feature fusion by Nishu Gupta, Jan Kubicek, Marek Penhaker, Mohammad Derawi

“…Discussion and conclusion: The integration of mammogram and DBT image data with advanced machine learning techniques, such as d-VAE and FENN, enhances diagnostic precision. …”
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MQGA: A quantitative analysis of brain network hubs using multi-graph theoretical indices by Hongzhou Wu, Zhenzhen Yang, Qingquan Cao, Pan Wang, Bharat B. Biswal, Benjamin Klugah-Brown

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Methods for processing and analyzing images of vascularized micro-organ and tumor systems by Stephanie J. Hachey, Christopher J. Hatch, Daniela Gaebler, Alexander G. Forsythe, Makena L. Ewald, Alexander L. Chopra, Zhangying Chen, Kapil Thapa, Melvin Hodanu, Jennifer S. Fang, Jennifer S. Fang, Jennifer S. Fang, Christopher C. W. Hughes, Christopher C. W. Hughes, Christopher C. W. Hughes

“…To manage the extensive imaging data generated, we created standardized, high-throughput workflows for image analysis. …”
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Quantification of training‐induced alterations in body composition via automated machine learning analysis of MRI images in the thigh region: A pilot study in young females by Saied Ramedani, Ebru Kelesoglu, Norman Stutzig, Hendrik Von Tengg‐Kobligk, Keivan Daneshvar Ghorbani, Tobias Siebert

“…The evaluation of the image data was performed by a machine learning system which is based on a 3D U‐Net‐based Convolutional Neural Network. …”
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Computational modeling of visual salience alteration and its application to eye-movement data by Yoshihisa Fujita, Toshiya Murai, Jun Miyata, Jun Miyata

“…The former provides sufficient performance for applying saliency map models to eye-movement data analysis, whereas the latter offers hypotheses on how neuronal abnormalities affect visual salience. …”
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Using an Improved PSO-SVM Model to Recognize and Classify the Image Signals by Ying Zhao, Guocheng Wei

“…In this paper, through the analysis of rough set theory and artificial intelligence network, as well as the role of the two in image recognition, the rough set theory and artificial intelligence network are organically combined, and a network based on rough set theory and artificial intelligence network is proposed. …”
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fMRI Analysis on Electroacupuncture on Tongli Acupoint in Healthy People by Lin LU, Wanzhang YANG, Yunhai QIU, Liping YE, Linling LI

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Distilling knowledge from graph neural networks trained on cell graphs to non-neural student models by Vasundhara Acharya, Bülent Yener, Gillian Beamer

“…A robust alternative to address this limitation involves leveraging cell graph representations, thereby enabling a more detailed analysis of local cell interactions. These cell graphs encapsulate the local spatial arrangement of cells in histopathology images, a factor proven to have significant prognostic value. …”
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Automatic Fracture Detection Convolutional Neural Network with Multiple Attention Blocks Using Multi-Region X-Ray Data by Rashadul Islam Sumon, Mejbah Ahammad, Md Ariful Islam Mozumder, Md Hasibuzzaman, Salam Akter, Hee-Cheol Kim, Mohammad Hassan Ali Al-Onaizan, Mohammed Saleh Ali Muthanna, Dina S. M. Hassan

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Bidirectional Mamba with Dual-Branch Feature Extraction for Hyperspectral Image Classification by Ming Sun, Jie Zhang, Xiaoou He, Yihe Zhong

“…The hyperspectral image (HSI) classification task is widely used in remote sensing image analysis. …”
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Towards automated and real-time multi-object detection of anguilliform fishes from sonar data using YOLOv8 deep learning algorithm by Tao Huang, Xiaoqin Zang, Grigoriy Kondyukov, Zhangshuan Hou, Guanze Peng, Joachim Pander, Josef Knott, Juergen Geist, Meklit Berihun Melesse, Paul Jacobson, Zhiqun Daniel Deng

“…However, a real-time and automated framework for detecting migrating eels in real-world applications is currently lacking. Leveraging imaging sonar as a reliable technology for fish passage monitoring in dark, turbid and high-flow environments, field data are acquired using imaging sonar and then converted to single sonar frames/images for subsequent analysis. …”
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SSATNet: Spectral-spatial attention transformer for hyperspectral corn image classification by Bin Wang, Gongchao Chen, Juan Wen, Linfang Li, Songlin Jin, Yan Li, Ling Zhou, Weidong Zhang

“…Hyperspectral images are rich in spectral and spatial information, providing a detailed and comprehensive description of objects, which makes hyperspectral image analysis technology essential in intelligent agriculture. …”
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