Positron emission tomography/computed tomography (PET/CT) imaging can simultaneously
acquire functional metabolic information and anatomical information of the human body …

Image segmentation is a fundamental and tedious task of computer vision. Because of
inherent noise and intensity inhomogeneity in real-world images, it remains a difficult …

Because there are many unlabeled samples in hyperspectral images and the cost of manual
labeling is high, this paper adopts semi-supervised learning method to make full use of …

This paper presents a novel global and local fuzzy image fitting (GLFIF) based active
contour model for image segmentation. First, we design two fitted images: global fuzzy fitted …

Point cloud registration is a hot research topic in the field of computer vision. In recent years,
the registration method based on evolutionary computation has attracted more and more …

Image registration is an important preprocessing step for many remote sensing image
processing applications, and its result will affect the performance of the follow-up …

This study proposes an approach for segmentation of skin lesions from dermoscopic images
based on fully convolutional neural network and active contour model (ACM). The …

Landslides are a critical geological phenomenon with devastating and catastrophic
consequences. With the recent advancements in the geoinformation domain, landslide …

This paper proposes a new global and local weighted signed pressure force (SPF) based
active contour model (ACM) to segment various types of images. First, by introducing the …

In this paper, a novel change detection approach based on multi-grained cascade forest
(gcForest) and multi-scale fusion for synthetic aperture radar (SAR) images is proposed. It …