Water body classification from high-resolution optical remote sensing (RS) images, aiming at
classifying whether each pixel of the image is water or not, has become a hot issue in the …

Recently, contour information largely improves the performance of saliency detection.
However, the discussion on the correlation between saliency and contour remains scarce. In …

Multi-scale features fusion plays a critical role in salient object detection. Most of existing
methods have achieved remarkable performance by exploiting various multi-scale features …

Recently, salient object detection in optical remote sensing images (RSI-SOD) has attracted
great attention. Benefiting from the success of deep learning and the inspiration of natural …

Image processing via convolutional neural network (CNN) has been developed rapidly for
remote sensing technology. Moreover, techniques for accurately extracting building …

Compared with the traditional object segmentation/detection, camouflaged object detection
is much more difficult due to the indefinable boundaries and high intrinsic similarities …

Skin detection involves identifying skin and non-skin areas in a digital image and is
commonly used in various applications, such as analyzing hand gestures, tracking body …

Abstract Deep Learning-based Unsupervised Salient Object Detection (USOD) mainly relies
on the noisy saliency pseudo labels that have been generated from traditional handcraft …

Recently, fully convolutional networks (FCNs) have made great progress in the task of
salient object detection and existing state-of-the-arts methods mainly focus on how to …

Contour information plays a vital role in salient object detection. However, excessive false
positives remain in predictions from existing contour-based models due to insufficient …