Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Chobola, Tomáš"'
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 diverse and unseen scenarios. In this paper, we introduce a novel approach
Externí odkaz:
http://arxiv.org/abs/2407.12511
Autor:
Chobola, Tomáš, Müller, Gesine, Dausmann, Veit, Theileis, Anton, Taucher, Jan, Huisken, Jan, Peng, Tingying
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 datasets of sharp ground truth images and trained with supervision. Sharp,
Externí odkaz:
http://arxiv.org/abs/2310.02097
Autor:
Chobola, Tomáš, Müller, Gesine, Dausmann, Veit, Theileis, Anton, Taucher, Jan, Huisken, Jan, Peng, Tingying
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 significant challenges in accurately analysing and interpreting the obtained
Externí odkaz:
http://arxiv.org/abs/2307.07998
Membership inference attacks aim to infer whether a data record has been used to train a target model by observing its predictions. In sensitive domains such as healthcare, this can constitute a severe privacy violation. In this work we attempt to ad
Externí odkaz:
http://arxiv.org/abs/2212.01082
We present a model for non-blind image deconvolution that incorporates the classic iterative method into a deep learning application. Instead of using large over-parameterised generative networks to create sharp picture representations, we build our
Externí odkaz:
http://arxiv.org/abs/2209.15377
MetaDL Challenge 2020 focused on image classification tasks in few-shot settings. This paper describes second best submission in the competition. Our meta learning approach modifies the distribution of classes in a latent space produced by a backbone
Externí odkaz:
http://arxiv.org/abs/2102.05176
One task that is often discussed in a computer vision is the mapping of an image from one domain to a corresponding image in another domain known as image-to-image translation. Currently there are several approaches solving this task. In this paper,
Externí odkaz:
http://arxiv.org/abs/2003.09149