Deep Learning (DL) has become one of the key approaches for dealing with many
challenges in medical imaging, which includes lung segmentation in Computed …

Image segmentation is an essential but critical component in low level vision, image
analysis, pattern recognition, and now in robotic systems. In addition, it is one of the most …

The development of the hyperspectral remote sensor technology allows the acquisition of
images with a very detailed spectral information for each pixel. Because of this …

Image segmentation is a fundamental task in computer vision and image processing. How to
efficiently decrease the effect such as high noise, low resolution and intensity inhomogeneity …

The occurrence of forest fires has increased significantly in recent years across the planet.
Events of this nature have resulted in the leveraging of new automated methodologies to …

Filling damaged pixels in satellite images is a key task present in many Remote Sensing
applications. As a representative example of image restoration issue, we can refer to the …

Existing deep learning-based interactive image segmentation methods have significantly
reduced the user's interaction burden with simple click interactions. However, they still …

Image classification and unsupervised image segmentation can be achieved using the
Gaussian mixture model. Although the Gaussian mixture model enhances the flexibility of …

The required number of users' actions and the response time can critically affect user
experience during interactive image segmentation. In this work, we revisit a recent graph …

The prominent properties owned by T-spline, such as flexibility, continuity, local refinement,
water tightness, make it extensively applied in Computer Aided Design (CAD)-and …