Abstract: This study explores the application of supervised and unsupervised autoencoders (AEs) to automate nuclei classification in clear cell renal cell carcinoma (ccRCC) images, a critical ...
Objective or purpose: To investigate an ensemble-based approach utilizing deep learning models for accurate and interpretable detection of Macular Telangiectasia Type 2 (MacTel) on optical coherence ...
Abstract: Heterogeneous images are captured through different wavelength bands, providing rich and complementary information for change detection (CD), and domain transformation has emerged as a ...
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