Researchers have developed a new artificial intelligence-based approach for detecting fatty deposits inside coronary arteries ...
Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...
A new software tool, ovrlpy, improves quality control in spatial transcriptomics, a key technology in biomedical research. Developed by the Berlin Institute of Health at Charité (BIH) in international ...
Deep Learning (DL) has emerged as a transformative approach in artificial intelligence, demonstrating remarkable capabilities in solving complex problems once considered unattainable. Its ability to ...
Abstract: We have developed an innovative framework for analyzing online public sentiment, referred to as the Online Public Opinion Situation Assessment (OPOSA) model. This model employs Deep Sparse ...
Synthetic Aperture Radar (SAR) imagery plays a critical role in all-weather, day-and-night remote sensing applications. However, existing SAR-oriented deep learning is constrained by data scarcity, ...
Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
Experiments were executed on NVIDIA A40 of 46068MiB memory in linux with torch==2.1.0+cu121, torch_geometric==2.3.1, torch-sparse==0.6.18+pt21cu121, and torchvision==0.16.0+cu121. The stkan is an ...
ABSTRACT: This work contributes to the development of intelligent data-driven approaches to improve intrusion management in smart IoT environments. The proposed model combines a hybrid ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results