Depth information is important for autonomous systems to perceive environments and
estimate their own state. Traditional depth estimation methods, like structure from motion …

Semantic image segmentation, which becomes one of the key applications in image
processing and computer vision domain, has been used in multiple domains such as …

Breast cancer is a lethal illness that has a high mortality rate. In treatment, the accuracy of
diagnosis is crucial. Machine learning and deep learning may be beneficial to doctors. The …

Abstract Recently, Neural Architecture Search (NAS) has successfully identified neural
network architectures that exceed human designed ones on large-scale image …

Crack detection is a critical task in monitoring and inspection of civil engineering structures.
Image classification and bounding box approaches have been proposed in existing vision …

Spatial pyramid pooling module or encode-decoder structure are used in deep neural
networks for semantic segmentation task. The former networks are able to encode multi …

The design of neural network architectures is an important component for achieving state-of-
the-art performance with machine learning systems across a broad array of tasks. Much …

Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

In this work we address the task of semantic image segmentation with Deep Learning and
make three main contributions that are experimentally shown to have substantial practical …

Since the last few decades, the number of road causalities has seen continuous growth
across the globe. Nowadays intelligent transportation systems are being developed to …