Deep neural networks (DNNs) have become a cornerstone of modern AI technology, driving a thriving field of research in ...
Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
White Blood Cell Classification is a deep learning project built with Python, TensorFlow, and Keras that classifies five types of WBCs from microscopic images using a CNN model. With advanced image ...
Abstract: Objective: Deep neural networks are widely used in the field of optical coherence tomography (OCT) to screen some common retinal diseases. However, for rare diseases with fewer cases for ...
1 Department of ophthalmology, JiuJiang City Key Laboratory of Cell Therapy, Jiujiang No. 1 People’s Hospital, JiuJiang, Jiangxi, China 2 Department of Otolaryngology, The Seventh Affiliated Hospital, ...
Crop classification is a key task in remote sensing, supporting agricultural monitoring, food security, and ecological management (Ding et al., 2023; Gentry et al., 2025). The Gaofen-1 (GF-1) ...
Abstract: Recent advances in deep learning have significantly improved hyperspectral image (HSI) classification. However, deep learning models for HSI classification typically rely on one-hot labels, ...
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