The standard treatment for the cancer is the radiotherapy where the organs nearby the target
volumes get affected during treatment called the Organs-at-risk. Segmentation of Organs-at …

This paper extends fully-convolutional neural networks (FCN) for the clothing parsing
problem. Clothing parsing requires higher-level knowledge on clothing semantics and …

Aerial Image Semantic segmentation based on convolution neural networks (CNNs) has
made significant process in recent years. Nevertheless, their vulnerability to adversarial …

The ability to semantically interpret hand-drawn line sketches, although very challenging,
can pave way for novel applications in multimedia. We propose SKETCHPARSE, the first …

An image semantic segmentation algorithm using fully convolutional network (FCN)
integrated with the recently proposed simple linear iterative clustering (SLIC) that is based …

Despite encouraging results have been achieved in human pose estimation in recent years,
it remains challenging problems. When the background is similar to the human body parts …

Enhancing network feature representation capabilities and reducing the loss of image
details have become the focus of semantic segmentation task. This work proposes the …

Automatic emotion recognition is active research in analyzing human's emotional state over
the past decades. It is still a challenging task in computer vision and artificial intelligence …

Deep learning (DL), a part of machine learning (ML), comprises a contemporary technique
for processing the images and analyzing the big data with promising outcomes. Deep …

Automatic reconstructing of neural circuits in the brain is one of the most crucial studies in
neuroscience. Connectomes segmentation plays an important role in reconstruction from …