Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...
What happens when intelligence moves off the cloud and onto the device? Edge AI Studio cuts latency, improves performance, ...
Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
📋 Project Overview This project presents a novel CBAM-guided channel pruning framework for efficient osteoporosis classification using knee X-ray images. The methodology achieves 55.9% parameter ...
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 ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...
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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