1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations
Tomáš Chobola, Yu Liu, Hanyi Zhang +2
Current deep learning-based low-light image enhancement methods often struggle with high-resolution images, and fail to meet the practical demands of visual perception across diver…
cs.CV2023
Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image Restoration
Tomáš Chobola, Gesine Müller, Veit Dausmann +4
Non-blind deconvolution aims to restore a sharp image from its blurred counterpart given an obtained kernel. Existing deep neural architectures are often built based on large datas…
cs.CV2023
LUCYD: A Feature-Driven Richardson-Lucy Deconvolution Network
Tomáš Chobola, Gesine Müller, Veit Dausmann +4
The process of acquiring microscopic images in life sciences often results in image degradation and corruption, characterised by the presence of noise and blur, which poses signifi…