This paper describes a real-time, high-performance deep-learning network to segment
internal damages of concrete members at the pixel level using active thermography. Unlike …

In machine learning, a generative model is responsible for generating new samples of data
in terms of a probabilistic model. Generative adversarial network (GAN) has been widely …

Sensor fusion plays a key part in autonomous surface vehicles, however, the high cost of
sensors makes the barrier of entry in this research field quite high. In this work, we present a …

The insufficient number of annotated thermal infrared (TIR) image datasets not only hinders
TIR image-based deep learning networks to have comparable performances to that of RGB …

Recent developments in pattern analysis have motivated many researchers to focus on
developing deep learning based solutions in various image processing applications. Fusing …

Abstract Structural Similarity Index Measure (SSIM) has been a very successful tool in image
processing and computer vision. After almost two decades, it is still the most popular method …

Offloading computationally heavy tasks from an unmanned aerial vehicle (UAV) to a remote
server helps improve battery life and can help reduce resource requirements. Deep learning …

Computer-generated imagery has been made more lifelike and misleading by new
Generative Adversarial Network (GAN) models, such as StyleGAN, posing severe risks to …

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 …

We introduce XoFTR a cross-modal cross-view method for local feature matching between
thermal infrared (TIR) and visible images. Unlike visible images TIR images are less …