Monitoring forest health typically relies on remote sensing tools such as light detection and ranging (LiDAR), radar, and ...

Millisecond Judgement In the ruthless arena of the digital economy, you do not have the luxury of time. Studies confirm that ...

Abstract: Recently, several models based on deep neural networks have achieved great success in terms of both reconstruction accuracy and computational performance for single image super-resolution.

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...

Deep learning-based image steganalysis has progressed in recent times, with efforts more concerted toward prioritizing detection accuracy over lightweight frameworks. In the context of AI-driven ...

Abstract: In this work, we investigate how to increase the resolution of color halftone images using convolutional neural networks (CNNs). As far as we know, this is the first work that increases ...