Detecting concealed explosives and chemical threats constitutes a critical challenge in global security, yet current ...

Deep neural networks (DNNs) have become a cornerstone of modern AI technology, driving a thriving field of research in ...

In a recent study, researchers from China have developed a chip-scale LiDAR system that mimics the human eye's foveation by dynamically concentrating high-resolution sensing on regions of interest ...

Monitoring forest health typically relies on remote sensing tools such as light detection and ranging (LiDAR), radar, and multispectral photography. While radar and LiDAR penetrate canopies to reveal ...

Abstract: Deep convolutional neural networks can use hierarchical information to progressively extract structural information to recover high-quality images. However, preserving the effectiveness of ...

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 ...

Abstract: Recent advancements in deep convolutional neural networks show significant improvements in single-image super-resolution (SR). Existing SR methods typically focus on designing deeper or ...

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 ...

In this tutorial, we will show you how to upscale an image using Copilot PC. Whether you want to take a large print of a picture, improve old photos, or crop a photo to focus on the content, you can ...

Objective: To extract and analyze the image features of two-dimensional ultrasound images and elastic images of four thyroid nodules by radiomics, and then further convolution processing to construct ...