The breakthrough brought by generative adversarial networks (GANs) in computer vision
(CV) applications has gained a lot of attention in different fields due to their ability to capture …

Machine Learning (ML) is now used in a range of systems with results that are reported to
exceed, under certain conditions, human performance. Many of these systems, in domains …

Image Dehazing is a fast growing research area with several practical applications.
Dehazing improves the image quality that has been affected due to the scattering …

Object detection is crucial in diverse autonomous systems like surveillance, autonomous
driving, and driver assistance, ensuring safety by recognizing pedestrians, vehicles, traffic …

For maritime autonomous surface ships, challenges exist in visual detection of ships in sea
foggy scenarios, thereby severely degrading visual detection autonomy. In this paper, math …

Hydroelectrochemical energy storage has the characteristics of high energy density, fast
response time, low maintenance cost, flexible and convenient installation, etc., and is a hot …

Most deep-learning-based vision models are trained and tested on clear images, avoiding
noisy, or hazy, images. However, these models may encounter degraded images. So, it is …

We introduce DeepCert, a tool-supported method for verifying the robustness of deep neural
network (DNN) image classifiers to contextually relevant perturbations such as blur, haze …

Robust semantic segmentation under adverse weather conditions is an open challenge in
autonomous driving applications. The main difficulty comes from the uncontrollability of the …

Unmanned Aerial Vehicle (UAV) inspection of transmission channels in mountainous areas
is susceptible to non-homogeneous fog, such as up-slope fog and advection fog, which …