The precise classification of land covers with hyperspectral imagery (HSI) is a major
research-focused topic in remote sensing, especially using unmanned aerial vehicle (UAV) …

Recently, deep learning (DL) models have become the main focus for the remote sensing
change detection tasks. Numerous publications on supervised and unsupervised DL-based …

As a specially designed tool and technique for the detection of image steganography, image
steganalysis conceals information under the carriers for covert communications. Being …

Poor real-time performance in multi-QR codes detection has been a bottleneck in QR code
decoding-based Internet of Things (IoT) systems. To tackle this issue, we propose in this …

Due to sensor design limitations and the influence of weather factors, it is currently
challenging to obtain remote sensing images with high temporal, spatial, and spectral …

Recently, deep neural networks (DNNs) have been widely used in hyperspectral image
change detection (HSI-CD). Generally, training such a DNN-based HSI-CD network often …

High-resolution remote sensing (RS) image change detection (CD) focuses on ground
surface changes. It has wide applications, including territorial spatial planning, urban region …

Deep learning-based hyperspectral image (HSI) change detection (CD) approaches have a
strong ability to leverage spectral-spatial-temporal information through automatic feature …

Citrus fruit are susceptible to Colletotrichum gloeosporioides infestation during postharvest
and shelf storage. Early and accurate detection of citrus anthracnose is conducive for …

The principal component analysis (PCA) and 2-D singular spectral analysis (2DSSA) are
widely used for spectral-and spatial-domain feature extraction in hyperspectral images …