Earth observation technologies offer non-intrusive solutions for monitoring complex and
risky sites, such as landfills. In particular, unmanned aerial vehicles (UAVs) offer the ability to …

In recent years, several superpixel-segmentation methods have been developed to
efficiently segment noisy images. However, these methods still face challenges such as high …

Image classification becomes a popular research area in computer vision due to the
increasing development of image indexing and retrieval tasks. This paper proposes a …

Recently, the detection and segmentation of salient objects that attract the attention of
human visual in images is determined by using salient object detection (SOD) techniques …

Magnetic resonance imaging (MRI) has high accuracy, which does not only causes less
damage to the patients, but also has a high spatial resolution. Besides, MRI is often used in …

This paper proposes a superpixel spatial intuitionistic fuzzy C-means (SSIFCM) clustering
algorithm to address the problems of misclassification, salt and pepper noise, and …

Colour is an important factor in the expression of recognizability and cultural identity of
regional cultural and creative design. At present, the colour recognition of regional …

This article presents a novel variational model based on fuzzy clustering and total variation
regularization for superpixel segmentation. Compared with the classical hard-labeled …

This article investigates whether higher classification accuracy can always be achieved by
utilizing a pre-trained deep learning model as the feature extractor in the Bag-of-Deep …

As an unsupervised clustering method with low overhead, Fuzzy C-means (FCM) clustering
has been widely used in a variety of image segmentation tasks. However, existing FCM …