The current development in deep learning is witnessing an exponential transition into
automation applications. This automation transition can provide a promising framework for …

Learning-based image inpainting methods have made remarkable progress in recent years.
Nevertheless, these methods still suffer from issues such as blurring, artifacts, and …

Medical image segmentation is a vital task in medical imaging, aiming to extract meaningful
and precise information from images. While traditional methods have been extensively used …

Image inpainting refers to the task of generating a complete, natural image based on a
partially revealed reference image. Recently, many research interests have been focused on …

The ocean is a crucial component of the Earth's system. It profoundly influences human
activities and plays a critical role in climate regulation. Our understanding has significantly …

Digitized methodologies in the recent era contribute to various fields of automation that used
to hold different interests and meanings of human life. Buildings with historical significance …

Face inpainting, the technique of restoring missing or damaged regions in facial images, is
pivotal for applications like face recognition in occluded scenarios and image analysis with …

Raw depth maps captured by depth sensors generally contain missing contents due to
glossy, transparent, and sparsity problems. Recent methods well completed flat regions of …

Achieving intelligent detection of defective leaves of hydroponic lettuce after harvesting is of
great significance for ensuring the quality and value of hydroponic lettuce. In order to …

Multi-class object detection in infrared images is important in military and civilian use. Deep
learning methods can obtain high accuracy but require a large-scale dataset. We propose a …