Semantic segmentation is a challenging task since it requires excessively more low-level
spatial information of the image compared to other computer vision problems. The accuracy …

Computer vision-based walking assistants are prominent tools for aiding visually impaired
people in navigation. Blind road segmentation is a key element in these walking assistant …

Semantic segmentation is the task of assigning a semantic class to each pixel in an image.
Due to the high annotation efforts for fully supervised learning of Deep Neural Networks …

Semantic segmentation of thermal infrared (ThIR) images is challenging because the
images considered in this task are highly complex. The discrimination of image regions is …

This work presents the analysis of semantically segmented, longitudinally, and spatially rich
thermal images collected at the neighborhood scale to identify hot and cool spots in urban …

Automating thermographic analysis for industrial and construction inspection is one of the
essential aspects of NDT 4.0 in industrial transformation. Thermal segmentation is a …

Single-image super-resolution (SISR), which maps a low-resolution observation to a high-
resolution image, has been extensively utilized in various computer vision applications. With …

As global populations soar and the climate warms, food supply management is an
increasingly critical problem. Precision agriculture, driven by on-site data collected from …

The dynamics of gaze coordination in natural contexts are affected by various properties of
the task, the agent, the environment, and their interaction. Artificial Intelligence (AI) lays the …

Disturbances such as inflammation, edema, and neural activation disorders in the human
body lead to local thermal asymmetries. With the recently developed thermal imaging …