Data-dependent visualization of biological networks in the web-browser with NDExEdit. by Florian Auer, Simone Mayer, Frank Kramer

“…Since the network data is only stored locally within the web browser, users can edit their private networks without concerns of unintentional publication. …”
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Saccades influence functional modularity in the human cortical vision network by George Tomou, Bianca R. Baltaretu, Amirhossein Ghaderi, J. Douglas Crawford

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VHR Multispectral Satellite Image Classification with Kolmogorov-Arnold Networks for Urban Applications by M. Fawzy, M. Fawzy, Á. Barsi

“…By efficiently encoding nonlinear relationships among features, KAN demonstrates potential in multilayered data analysis tasks such as multi and hyper-spectral remotely sensed image classification. …”
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A Composite Network for CS ISAR Integrating Deep Adaptive Sampling and Imaging by Lianzi Wang, Ling Wang, Miguel Heredia Conde, DaiYin Zhu

“…The CS ISAR imaging with adaptive sampling consists of sampling and reconstruction networks, where the sampling network compresses the radar data by a convolutional neural network, and the reconstruction network mainly performs the image reconstruction by convolutional dictionary learning. …”
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Deep convolution neural network model in problem of crack segmentation on asphalt images by B. V. Sobol, A. N. Soloviev, P. V. Vasiliev, L. A. Podkolzina

“…Manual evaluation and analysis of the data obtained may take unacceptably long time. …”
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Deep Convolutional Network Based Machine Intelligence Model for Satellite Cloud Image Classification by Kalyan Kumar Jena, Sourav Kumar Bhoi, Soumya Ranjan Nayak, Ranjit Panigrahi, Akash Kumar Bhoi

“…As a huge number of satellites revolve around the earth, a great probability exists to observe and determine the change phenomena on the earth through the analysis of satellite images on a real-time basis. …”
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Securing face images in UAV networks using chaos and DNA cryptography approach by Saba Inam, Shamsa Kanwal, Eaman Amin, Omar Cheikhrouhou, Monia Hamdi

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Atmospheric Turbulence Intensity Image Acquisition Method Based on Convolutional Neural Network by Yuan Mu, Liangping Zhou, Shiyong Shao, Zhiqiang Wang, Pei Tang, Zhiyuan Hu, Liwen Ye

“…By processing the acquired spot image data, the channel attention and spatial attention mechanisms are utilized, and the convolutional neural network learns the interdependence between the channel and space of the feature image and adaptively recalibrates the feature response in terms of the channel to increase the contribution of the foreground spot and suppress the background features. …”
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THE EMPIRICAL COMPARISON OF DEEP NEURAL NETWORK OPTIMIZERS FOR BINARY CLASSIFICATION OF OCT IMAGES by R. Loganathan, S. Latha

“…To classify normal vs. AMD binary data on the optical coherence tomography (OCT) image dataset, the main objective of this work is to determine which optimizer yields the minimum loss and maximum accuracy throughout the training and testing phases of CNN, DNN, and VGG16 models. …”
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Applying neural networks in coordinated group signal transformation to improve image quality by E.A. Lopukhova, G.S. Voronkov, I.V. Kuznetsov, V.V. Ivanov, R.V. Kutluyarov, A.Kh. Sultanov, E.P. Grakhova

“…The rapid development of the Internet of Things and wireless sensor networks combined with the introduction of image analysis systems and computer vision technologies has led to the emergence of a new class of systems – multimedia Internet of Things and multimedia wireless sensing networks. …”
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Guided Texture Transfer Network for Mid-Infrared Satellite Image Super Resolution by Yeji Jeon, Youkyung Han, Kwang-Jae Lee, Yeseul Kim, Hanul Kim

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MSNet: A multispectral-image driven rapeseed canopy instance segmentation network by Yuang Yang, Xiaole Wang, Fugui Zhang, Zhenchao Wu, Yu Wang, Yujie Liu, Xuan Lv, Bowen Luo, Liqing Chen, Yang Yang

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ENHANCED POLSAR IMAGE CLASSIFICATION USING DEEP CONVOLUTIONAL AND TEMPORAL CONVOLUTIONAL NETWORKS by Batool Anwar, Mohamed M. Morsey, Islam Hegazy, Zaki T. Fayed, Taha El-Arif

“… A new framework in the form of Polarimetric Synthetic Aperture Radar (PolSAR) image classification, where deep Convolutional Neural Networks (CNNs) were integrated with the traditional Machine Learning (ML) techniques under a Temporal Convolutional Network (TCN) architecture, was introduced in the paper. …”
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Hyperspectral image super-resolution via joint network with spectral-spatial strategy by Yaxin Dong, Bo Yang, Cong Liu, Zemin Geng, Taiping Wang

“…Hyperspectral image (HSI) super-resolution (SR) faces significant challenges due to the inherent difficulty in acquiring large-scale training data and the complex spectral-spatial relationships in HSIs that conventional deep-learning-based methods often fail to fully exploit. …”
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YOLOv8 vs RetinaNet vs EfficientDet: A Comparative Analysis for Modern Object Detection by Sana Fatima, Najmi Ghani Haider, Rizwan Riaz

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A Physics-Enhanced Network for Predicting Sequential Satellite Images of Typhoon Clouds by Jiawei Yuan, Liling Zhao, Runling Yu, Xiaoqin Lu, Min Xia, Yi Liu, Yuru Wang, Xinyue Wang

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EfficientNet-B0 outperforms other CNNs in image-based five-class embryo grading: a comparative analysis by Vincent Jaehyun Shim, Hosup Shim, Sangho Roh

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Research into the Application of ResNet in Soil: A Review by Wenjie Wu, Lijuan Huo, Gaiqiang Yang, Xin Liu, Hongxia Li

“…With the rapid advancement of deep learning technology, the residual networks technique (ResNet) has made significant strides in the field of image processing, and its application in soil science has been steadily increasing. …”
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Multi-Dimensional Lithology Identification Method Based on Microresistivity Image Logging by LIU Juan, MIN Xuanlin, QI Zhongli, YI Jun, LAI Fuqiang, ZHOU Wei

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Method for Automatic Determination of a 3D Trajectory of Vehicles in a Video Image by I. G. Zubov, N. A. Obukhova

“…The vehicle pose estimation had an accuracy of 89 % on an open Carvana image dataset.Conclusion. A new approach for vehicle pose estimation was proposed, involving the transition from end-to-end learning of neural networks to resolve several problems at once, e.g., localization, classification, segmentation, and angle of view, towards cascade analysis of information. …”
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