Emotion recognition plays a significant role in cognitive psychology research. However,
measuring emotions is a challenging task. Thus, several approaches have been designed …

Images captured in hazy environments need to be processed to increase their contrast and
colour integrity. Dehazing, sometimes referred to as haze removal is an important pre …

Nowadays, researchers use vision-based measurement tools to record, detect, and monitor
an atmospheric phenomenon called haze. It impedes the proper functioning of many …

Visibility issues in intelligent transportation systems are exacerbated by bad weather
conditions such as fog and haze. It has been observed from recent studies that major road …

Single-image dehazing is a challenging task in several machine-vision applications.
Methods based on physical models and prior knowledge fail under certain conditions …

Single-image dehazing plays a significant preprocessing role in machine vision tasks. As
the dark-channel-prior method will fail in the sky region of the image, resulting in …

Artificial lateral line (ALL) sensors hold the potential to enhance the perception abilities of
robotic fish by capturing surface pressure gradients and identifying near-field object, such as …

Haze contamination is a quite common issue in nighttime light remote sensing (NTLRS)
images. It significantly limits the application of NTLRS images, especially in human activity …

Deep learning is a powerful tool in the realm of low-level computer vision and has achieved
significant success in image dehazing. However, previous works have predominantly …

Unpaired image dehazing models based on Cycle-Consistent Adversarial Networks
(CycleGAN) typically consist of two cycle branches: dehazing-rehazing branch and hazing …