UIESNN is a scale-aware spiking network that adds hierarchical multi-scale pooling to membrane dynamics in a residual architecture, achieving state-of-the-art results among SNN methods on EUVP and LSUI benchmarks.
Fast underwater image enhancement for improved visual perception
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
dataset 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
dataset 1polarities
use dataset 1representative citing papers
UDehaze-iT is a lightweight deep network that enhances underwater images by implicitly estimating depth and deriving transmission via learnable Beer-Lambert attenuation coefficients, achieving competitive results on UIEB and UFO-120 with 0.9M parameters.
citing papers explorer
-
An Underwater Dehazing Network with Implicit Transmission Estimation
UDehaze-iT is a lightweight deep network that enhances underwater images by implicitly estimating depth and deriving transmission via learnable Beer-Lambert attenuation coefficients, achieving competitive results on UIEB and UFO-120 with 0.9M parameters.