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169 articles for “Images Classification”
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Research ArticleOpen accessIn the keywordsCPF-Net: Cross-modal CT and Pathology Guided Feature Learning for CT-based Lung Cancer Subtype ClassificationPeizhi Tan, Debiao YanAccurate classification of lung cancer subtypes from CT images remains challenging due to the subtle radiological differences between adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). We propose CPF-Net, a deep learning framework that integrates CT and pathological information through a Linear Spatial Reduction Attention (LSRA) module. The framework processes whole slide images using a modified CTransPath architecture for pathological feature … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 3 · 23 Jan 2026 · 1,856 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRemote Sensing Image Classification Using Convolutional Neural Network (CNN) and Transfer Learning TechniquesMustafa Majeed Abd Zaid, Ahmed Abed Mohammed, Putra SumariThis study investigates the classification of aerial images depicting transmission towers, forests, farmland, and mountains. To complete the classification job, features are extracted from input photos using a Convolutional Neural Network (CNN) architecture. Then, the images are classified using Softmax. To test the model, we ran it for ten epochs using a batch size of 90, the Adam optimizer, and … …Journal of Computer Science, Vol. 21, Issue 3 · 11 Feb 2025 · 10,117 accessesView PDFCite
Review ArticleOpen accessIn the keywordsChallenges of Breast Cancer Detection Based on Histopathology ImagesAlaa Mohamed Youssef, Aliaa Abdel-Haleim Abdel-Razik Youssif, Wessam El BehaidyArtificial Intelligence (AI) is rapidly evolving every day to become increasingly potent and dependable. AI systems are becoming more sophisticated and are being utilized across various domains with the goal of enhancing human existence. Within the healthcare system, artificial intelligence finds application in handling and documenting large volumes of medical data, conducting analyses of healthcare systems, advancing pharmaceutical development, and … …Journal of Computer Science, Vol. 20, Issue 7 · 17 Apr 2024 · 4,942 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Hybrid Model of Bidirectional Long-Short Term Memory and CNN for Multivariate Time Series Classification of Remote Sensing DataSawsan Morkos GharghoryClassification of multivariate time series has got massive attention in the last decade. The traditional modeling classifiers are complicated patterns and are incompetent to capture the dependencies of multivariate time series data. To include both of the effective features and the embedded relationships in the multivariate time series, a new hybrid model which incorporates both Convolutional Neural Network (CNN) and … …Journal of Computer Science, Vol. 17, Issue 9 · 29 Sep 2021 · 6,686 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCharacterization of the Earth's Surface State by Unsupervised Classification: Case of Vegetated, Aquatic and Mineral SurfacesJean-Claude Okaingni, Sié Ouattara, Adles Kouassi, Alain ClémentIn this study, we propose an unsupervised classification scheme based on the Dempster-Shafer Theory (TDS) and the Dezert-Smarandache Theory (DSmT) to characterize vegetated, aquatic and mineral surfaces. From pre-processed ASTER satellite images (georeferencing, geometric correction and 15 m re-sampling), neo-channels were produced by determining the spectral indices NDVI, MNDWI and NDBaI, considered as sources of information for classification of a … …American Journal of Applied Sciences, Vol. 15, Issue 7 · 27 Aug 2018 · 8,176 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Pre-Processing Techniques to Improve DBT Classification Accuracy With CNN ResNet-50Qodri Aziz, Slamet Riyadi et al.Digital Breast Tomosynthesis (DBT) is a three-dimensional imaging technology that is meant to determine breast cancer more accurately than regular mammograms. But low contrast and noise can make DBT images less clear, which can make deep learning-based classification less accurate. This study seeks to assess the impact of diverse preprocessing techniques on breast cancer classification outcomes utilizing the ResNet-50 Convolutional … …Journal of Computer Science, Vol. 22, Issue 10 · 21 Oct 2026 · 349 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief NetworkGeetha M. N, Barkathulla A, S. Nandhini Devi et al.Automated CKD is a rapidly expanding non-communicable ailment that significantly contributes to global mortality and morbidity. CKD impacts more than 10% of the worldwide population, leading to millions of deaths annually. This paper proposes an enhanced deep learning model for renal disease detection that integrates convolutional and involution layers to enhance classification accuracy. CKD is a worldwide health issue characterised … …Journal of Computer Science, Vol. 22, Issue 10 · 9 Oct 2026 · 749 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeveraging Modified Cascaded Fully Convolutional Neural Networks and Optimized Swin U-Net for Liver Lesion PredictionSugandha Chakraverti, Tejaswi Khanna, Vijay ShuklaLiver lesions are abnormal growths that can develop for various reasons, some of which are noncancerous (benign) while others are cancerous. Machine learning and, deep learning techniques are employed for liver health assessment and lesion detection, but the quality and, diversity of training data can hinder the performance, leading to overfitting or underfitting. These models often need extensive pre-processing and … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 372 accessesView PDFCite
Research ArticleOpen accessIn the abstractRIA-ViT: A Residual Inception Atrous Vision Transformer for Detection of Gallbladder Cancer from CT ImagesAbhishek Sehrawat, Anita Gupta, Vishnupriya, Varun P. GopiGallbladder Cancer (GBC) is a rare but highly aggressive malignancy of the biliary system. In early-stage gallbladder cancer, there are neither overt symptoms nor specific signs. In most patients, it is diagnosed late, resulting in poor outcomes. Even when imaging is available, diagnosing GBC remains difficult because its features overlap with those of non-neoplastic gallbladder pathologies. Furthermore, the overlap between … …Journal of Computer Science, Vol. 22, Issue 10 · 6 Oct 2026 · 413 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetermination of Crop Yield Detection and Prediction With Multimodal Data Using Fusion TechniquesKutlwano Sedimo, Rajalakshmi Selveraj, Venumadhav Kuthadi, Thulaganyo DimakatsoMost often, soil, environmental, and agronomic data are used in pieces, hence limiting the performance of crop selection and yield forecasting. This study develops an integrated, fusion-based framework that combines soil image classification, environmental feature analysis, and input-driven yield prediction to support precise agricultural decision-making. The system consists of three major modules: (i) a CNN for the classification of soil … …Journal of Computer Science, Vol. 22, Issue 10 · 5 Oct 2026 · 481 accessesView PDFCite