A review of SAR tomography by Xin Zhao, Jie Dong, Yanghai Yu, Mingsheng Liao, Lu Zhang, Jianya Gong

“…Then, three key aspects of tomographic processing—3D imaging algorithm, calibration of phase errors, and impact of temporal decorrelation – are detailed and analyzed. …”
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GeoAT: Geometry-Aware Attention Feature Matching Network by Yan Li, Yingdan Wu, Yang Ming, Yong Zhang, Zhesheng Cheng

“…However, in the context of image matching with large deformations, attention often suffers from divergence issues. …”
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On the Search for Supersingular Elliptic Curves and Their Applications by Ismel Martinez-Diaz, Rashad Ali, Muhammad Kamran Jamil

“…The key components of replacement, which is a fundamental step in the encryption process that shuffles and encrypts the data inside images, are S-boxes. …”
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Date Fruit Detection and Classification Based on Its Variety Using Deep Learning Technology by Ahad Almutairi, Jawza Alharbi, Shouq Alharbi, Haifa F. Alhasson, Shuaa S. Alharbi, Shabana Habib

“…The purpose of this study was to use Deep Learning technology to detect and classify them by using the You Only Look Once (YOLO) algorithm. Different YOLO models (YOLOv5, YOLOv7, YOLOv8) have been trained using 1735 images with 9 types of date fruits. …”
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Radiometric landscape: a new conceptual framework and operational approach for landscape characterisation and mapping by Louise Lemettais, Samuel Alleaume, Sandra Luque, Anne-Élisabeth Laques, Yonas Alim, Laurent Demagistri, Agnès Bégué

“…The RS-ELVs are then processed according to geographic object-based image analysis (GEOBIA) approach to produce a radiometric landscape map. …”
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3D-CNN with Multi-Scale Fusion for Tree Crown Segmentation and Species Classification by Jiayao Wang, Zhen Zhen, Yuting Zhao, Ye Ma, Yinghui Zhao

“…The study consists of two main processes: (1) combining semantic segmentation algorithms (U-Net and Deeplab V3 Plus) with watershed transform (WTS) for tree crown detection (U-WTS and D-WTS algorithms); (2) resampling the original images to different pixel densities (16 × 16, 32 × 32, and 64 × 64 pixels) and inputting them into five 3D-CNN models (ResNet10, ResNet18, ResNet34, ResNet50, VGG16). …”
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The Fermentation Degree Prediction Model for Tieguanyin Oolong Tea Based on Visual and Sensing Technologies by Yuyan Huang, Jian Zhao, Chengxu Zheng, Chuanhui Li, Tao Wang, Liangde Xiao, Yongkuai Chen

“…In this study, using Tieguanyin oolong tea as the research object, features including the tea water loss rate, aroma, image color, and texture were obtained using weight sensors, a tin oxide-type gas sensor, and a visual acquisition system. …”
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Disassembly of Distribution Transformers Based on Multimodal Data Recognition and Collaborative Processing by Li Wang, Feng Chen, Yujia Hu, Zhiyao Zheng, Kexin Zhang

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Robust SAR Change Detection Using Hierarchical Clustering With Adaptive Parameter Tuning by Ahidjo Abdoulaye, Alejandro C. Frery, Mingyang Ma, Shaohui Mei

“…Traditional clustering-based methods often make strong assumptions about data structure, struggle with noise, and fail to handle the intricate characteristics of radar images effectively. Furthermore, deriving change maps directly from the difference image can introduce confusion and increase detection errors. …”
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Discrepancy in Metabolic Dysfunction–Associated Steatotic Liver Disease Prevalence in a Large Northern California Cohort by Luis A. Rodriguez, Lue-Yen S. Tucker, Varun Saxena, Theodore R. Levin

“…Annual MASLD prevalence was identified based on International Classification of Diseases, Ninth or Tenth Revision, Clinical Modification diagnosis codes, the application of natural language processing of all radiology imaging report text that included the liver, and the application of the Dallas Steatosis Index, a MASLD prediction algorithm. …”
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Diagnosis and Detection of Alzheimer’s Disease Using Learning Algorithm by Gargi Pant Shukla, Santosh Kumar, Saroj Kumar Pandey, Rohit Agarwal, Neeraj Varshney, Ankit Kumar

“…Selective clipping, grayscale image conversion, and histogram equalization techniques were used to pre-process the images. …”
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Digital technologies for signal radio vision and radio monitoring by M. S. Kostin, K. A. Boikov

“…The study is based on statistical radiophysics methods, time-frequency approaches for wavelet transformation of USP radio images, numerical electrodynamic methods for creating digital twins of small-sized objects, as well as neural network authentication algorithms based on the cumulant theory of pole-genetic and resonant physically unclonable functions used in identifying signal radio images.Results. …”
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Intelligent recognition of tobacco leaves states during curing with deep neural network by Qiang Xu, Yanling Zhang, Aiguo Wang, Guangqing Chen, Xianjie Cai, Shuoye Zhou, Junying Li, Baofeng Jin, Ding Yan, Jiajie Huang, Zuxiao Chen, Heng Zhang, Jianwei Wang, Weimin Guo, Jianjun Liu

“…Moreover, the previous research typically used a limited number of non-industrial images for training, creating a significant disparity with the images encountered in actual applications.MethodsTo investigate the potential of deep learning algorithms in identifying the morphological states of tobacco leaves in real industrial scenarios, a comprehensive and large-scale dataset was developed in this study. …”
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Game Narratives as Tools for Shaping Political Discourse Amidst Information Wars: The Case of the Ukrainian Conflict by Daniil A. Fedotov, Stanislav I. Kaminsky

“…The political images of Russia built into their structure are identified and systematized, and strategic approaches to preventing information risks and optimizing socio-political communications are developed. …”
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Hybrid quadratic diagonal algorithm for thinning contour lines by Mamatov Narzullo, Jalelova Malika, Fayziev Vohid, Samijonov Abdurashid, Samijonov Boymirzo

“…Contour thinning algorithms can reduce the amount of data to be processed and increase processing speed. …”
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Deep Learning in Visual Computing and Signal Processing by Danfeng Xie, Lei Zhang, Li Bai

“…Nowadays, researchers have intensively investigated deep learning algorithms for solving challenging problems in many areas such as image classification, speech recognition, signal processing, and natural language processing. …”
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A comparative analysis of fault detection and process diagnosis methods based on a signal processing paradigm by Dorel Aiordăchioaie

“…In the time–frequency domain, the coefficients of the time–frequency transforms define digital images, which are further processed. For testing, the methods are evaluated with real recorded data from bearings with several types and sizes of faults, i.e., incipient, medium, advanced, and large. …”
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A small‐target traffic sign detection algorithm based on partial conv and atrous spatial pyramid by Yuqi Li, Zijian Wang, Han Zhang, Xinpeng Yao, Zhou Zhou, Xin Cheng

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Comparison of radiological interpretation made by veterinary radiologists and state-of-the-art commercial AI software for canine and feline radiographic studies by Yero S. Ndiaye, Yero S. Ndiaye, Peter Cramton, Peter Cramton, Chavdar Chernev, Chavdar Chernev, Axel Ockenfels, Axel Ockenfels, Tobias Schwarz

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An overview of the activation functions used in deep learning algorithms by Mete Çelik, Kemal Adem, Serhat Kılıçarslan

“…Deep learning models are of particular importance in analyzing big data with numerous parameters and forecasting and are useful for image processing, natural language processing, object recognition, and financial forecasting. …”
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