The uncertainty of power systems is rapidly increasing with the continuing development of
renewable energy. Probabilistic power flow (PPF) is an effective tool for addressing these …

With the development of remote sensing imaging technology, remote sensing images with
high-resolution and complex structure can be acquired easily. The classification of remote …

Deep learning methods have recently found widespread adoption for remote sensing tasks,
particularly in image or pixel classification. Their flexibility and versatility has enabled …

In this paper, we propose an unsupervised method for hyperspectral remote sensing image
segmentation. The method exploits the mean-shift clustering algorithm that takes as input a …

Efficient and automated data acquisition techniques, as well as intelligent and accurate data
processing and analysis techniques, are essential for the advancement of precision …

Remote sensing image scene classification is an important task of remote sensing image
interpretation, which has recently been well addressed by the convolutional neural network …

In recent years, deep-learning-based hyperspectral image (HSI) classification methods have
achieved significant development and gradually become widely applied. The existing …

In recent years, there has been a growing emphasis on assessing and ensuring the quality
of horticultural and agricultural produce. Traditional methods involving field measurements …

Hyperspectral anomaly detection (AD) is an important technique of unsupervised target
detection and has significance in real situations. Due to the high dimensionality of …

Image registration is an essential pre-processing step for several computer vision problems
like image reconstruction and image fusion. In this paper, we present a review on image …