Impact Statement: Deep learning has achieved state-of-the-art accuracy for an array of computer vision tasks. However, enabling CNNs on edge—edge AI— poses significant challenges in terms of resource ...

The GNN models, where we did not apply data augmentation, include two layers with 32 and 64 neurons. Leaky ReLU activation functions, a learning rate of 0.0005, and an L1Loss function were applied. We ...

Abstract: Deep Convolutional Neural Networks - also known as DCNN - are powerful models for different visual pattern classification problems. Many works in this field use image augmentation at the ...

(U.S. Navy photo) The Navy is working with the Defense Innovation Unit to use artificial intelligence and machine learning to process the vast quantity of data it receives and make sense of it for ...