CDRSHNET: VARIANCE-GUIDED MULTISCALE AND SELF-ATTENTION FUSION WITH HYBRID LOSS FUNCTION TO RESTORE TRAFFIC-SIGN IMAGES CAPTURED IN ADVERSE CONDITIONS

CDRSHNET: VARIANCE-GUIDED MULTISCALE AND SELF-ATTENTION FUSION WITH HYBRID LOSS FUNCTION TO RESTORE TRAFFIC-SIGN IMAGES CAPTURED IN ADVERSE CONDITIONS

This paper proposes a CDRSHNet (CodecDirtyRainyShadowHazeNetwork) architecture with a fusion of self-attention (SA) and variance-guided multiscale attention (VGMA) mechanism to restore traffic sign images captured in challenging weather conditions including raindrops, shadows, haze, blurry images fr...

Full description

Bibliographic Details
Main Authors: Milind Vijay Parse, Dhanya Pramod
Format: Article
Language:English
Published: Scientific Research Support Fund of Jordan (SRSF) and Princess Sumaya University for Technology (PSUT) 2024-03-01
Series:Jordanian Journal of Computers and Information Technology
Subjects:
image restoration
challenging weather conditions
variance guided multiscale attention
custom loss function
Online Access:https://www.jjcit.org/?mno=177025

Internet

https://www.jjcit.org/?mno=177025

Similar Items