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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Graph-Aware Multimodal Deep Learning for Classification of Diabetic Retinopathy Images by Amina Zedadra, Ouarda Zedadra, Mahmoud Yassine Salah-Salah, Antonio Guerrieri

“…Traditional diagnostic methods primarily rely on single-modality data, such as retinal images, or the analysis of image features, which may limit diagnostic accuracy. …”
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Evolution of deep learning tooth segmentation from CT/CBCT images: a systematic review and meta-analysis by Wai Ying Kot, Sum Yin Au Yeung, Yin Yan Leung, Pui Hang Leung, Wei-fa Yang

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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 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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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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Evaluating pedestrian crossing safety: Implementing and evaluating a convolutional neural network model trained on paired aerial and subjective perspective images by Dylan Russon, Antoine Guennec, Juan Naredo-Turrado, Binbin Xu, Cédric Boussuge, Valérie Battaglia, Benoit Hiron, Emmanuel Lagarde

“…The analysis reveals that the ConvNextV2 model, in particular, demonstrates superior performance across most tasks, despite challenges such as data imbalance and the complex nature of variables like visibility and parking proximity.The findings highlight the potential of convolutional neural networks in improving pedestrian safety by enabling scalable and objective evaluations of crossings. …”
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A fashion product recommendation based on adaptive VPKNN-NET algorithm without fuzzy similar image by R. Sabitha, D. Sundar

“…The model integrates deep visual feature extraction using a pre-trained VGG16 Convolutional Neural Network (CNN), dimensionality reduction through Principal Component Analysis (PCA), and a modified K-Nearest Neighbors (KNN) algorithm that combines Euclidean and cosine similarity metrics to enhance visual similarity assessment.ResultsExperiments were conducted using the “Fashion Product Images (Small)” dataset from Kaggle. …”
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Analysis of Bladder Cancer Staging Prediction Using Deep Residual Neural Network, Radiomics, and RNA-Seq from High-Definition CT Images by Yao Zhou, Xingju Zheng, Zhucheng Sun, Bo Wang

“…Data for this study, including CT images and RNA-Seq datasets for 82 high-grade bladder cancer patients, were sourced from the TCIA and TCGA databases. …”
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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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Self-supervised denoising method for single neutron image based on the S2S-NR network by Wangtao Yu, Peng Xu, Xinghui Cai, Man Zhou, Jie Bao

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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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MFA-SCDNet: A Semantic Change Detection Network for Visible and Infrared Image Pairs by Xingyu Li, Jiulu Gong, Jianxiong Wen, Zepeng Wang

“…Semantic Change Detection (SCD) in remote sensing imagery is a common technique for monitoring surface dynamics. However, geospatial data acquisition increasingly involves the collection of visible and infrared images. …”
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Enhanced Deep Learning for Robust Stress Classification in Sows from Facial Images by Syed U. Yunas, Ajmal Shahbaz, Emma M. Baxter, Mark F. Hansen, Melvyn L. Smith, Lyndon N. Smith

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Urban Environment and Momentary Psychological States: A Micro-Scale Study on a University Campus with Network Analysis by Fanxi Wang, Feng Qi

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Brain Perfusion Analysis Method using Computed Tomography Images by E. Khudiakova, A. Gavrilov, A. Krylov

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Multi-Level Intertemporal Attention-Guided Network for Change Detection in Remote Sensing Images by Shuo Liu, Qinyu Zhang, Yuhang Zhang, Xiaochen Niu, Wuxia Zhang, Fei Xie

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Performance Analysis of Resampling Techniques for Overcoming Data Imbalance in Multiclass Classification by Anggit Larasati, Sugiyarto Surono, Aris Thobirin, Deshinta Arrova Dewi

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A privacy preserving machine learning framework for medical image analysis using quantized fully connected neural networks with TFHE based inference by Sadhana Selvakumar, B. Senthilkumar

“…This paper presents a privacy-preserving machine learning (PPML) framework using a Fully Connected Neural Network (FCNN) for secure medical image analysis using the MedMNIST dataset. …”
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