Comparing deep learning models for low-light natural scene image enhancement and their impact on object detection and classification: Overview, empirical …
R Al Sobbahi, J Tekli - Signal Processing: Image Communication, 2022 - Elsevier
Low-light image (LLI) enhancement is an important image processing task that aims at
improving the illumination of images taken under low-light conditions. Recently, a …
improving the illumination of images taken under low-light conditions. Recently, a …
A survey on cancer detection via convolutional neural networks: Current challenges and future directions
Cancer is a condition in which abnormal cells uncontrollably split and damage the body
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …
Retinexformer: One-stage retinex-based transformer for low-light image enhancement
When enhancing low-light images, many deep learning algorithms are based on the Retinex
theory. However, the Retinex model does not consider the corruptions hidden in the dark or …
theory. However, the Retinex model does not consider the corruptions hidden in the dark or …
Beyond brightening low-light images
Images captured under low-light conditions often suffer from (partially) poor visibility.
Besides unsatisfactory lightings, multiple types of degradation, such as noise and color …
Besides unsatisfactory lightings, multiple types of degradation, such as noise and color …
Implicit neural representation for cooperative low-light image enhancement
The following three factors restrict the application of existing low-light image enhancement
methods: unpredictable brightness degradation and noise, inherent gap between metric …
methods: unpredictable brightness degradation and noise, inherent gap between metric …
Kindling the darkness: A practical low-light image enhancer
Images captured under low-light conditions often suffer from (partially) poor visibility.
Besides unsatisfactory lightings, multiple types of degradations, such as noise and color …
Besides unsatisfactory lightings, multiple types of degradations, such as noise and color …
Diabetic retinopathy fundus image classification and lesions localization system using deep learning
WL Alyoubi, MF Abulkhair, WM Shalash - Sensors, 2021 - mdpi.com
Diabetic retinopathy (DR) is a disease resulting from diabetes complications, causing non-
reversible damage to retina blood vessels. DR is a leading cause of blindness if not …
reversible damage to retina blood vessels. DR is a leading cause of blindness if not …
Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images
Regular screening for the early detection of common chronic diseases might benefit from the
use of deep-learning approaches, particularly in resource-poor or remote settings. Here we …
use of deep-learning approaches, particularly in resource-poor or remote settings. Here we …
DSLR: Deep stacked Laplacian restorer for low-light image enhancement
S Lim, W Kim - IEEE Transactions on Multimedia, 2020 - ieeexplore.ieee.org
Various images captured in complicated lighting conditions often suffer from deterioration of
the image quality. Such poor quality not only dissatisfies the user expectation but also may …
the image quality. Such poor quality not only dissatisfies the user expectation but also may …
Lightening network for low-light image enhancement
Low-light image enhancement is a challenging task that has attracted considerable
attention. Pictures taken in low-light conditions often have bad visual quality. To address the …
attention. Pictures taken in low-light conditions often have bad visual quality. To address the …