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 Review of Biosensors and Artificial Intelligence in Healthcare and Their Clinical Significance
In the past decade, a substantial increase in medical data from various sources, including
wearable sensors, medical imaging, personal health records, and public health …
wearable sensors, medical imaging, personal health records, and public health …
[HTML][HTML] Swin transformer for fast MRI
Magnetic resonance imaging (MRI) is an important non-invasive clinical tool that can
produce high-resolution and reproducible images. However, a long scanning time is …
produce high-resolution and reproducible images. However, a long scanning time is …
[HTML][HTML] Artificial intelligence for visually impaired
J Wang, S Wang, Y Zhang - Displays, 2023 - Elsevier
The eyes are an essential tool for human observation and perception of the world, helping
people to perform their tasks. Visual impairment causes many inconveniences in the lives of …
people to perform their tasks. Visual impairment causes many inconveniences in the lives of …
Hqg-net: Unpaired medical image enhancement with high-quality guidance
Unpaired medical image enhancement (UMIE) aims to transform a low-quality (LQ) medical
image into a high-quality (HQ) one without relying on paired images for training. While most …
image into a high-quality (HQ) one without relying on paired images for training. While most …
Artificial intelligence and biosensors in healthcare and its clinical relevance: A review
Data generated from sources such as wearable sensors, medical imaging, personal health
records, and public health organizations have resulted in a massive information increase in …
records, and public health organizations have resulted in a massive information increase in …
Rformer: Transformer-based generative adversarial network for real fundus image restoration on a new clinical benchmark
Ophthalmologists have used fundus images to screen and diagnose eye diseases.
However, different equipments and ophthalmologists pose large variations to the quality of …
However, different equipments and ophthalmologists pose large variations to the quality of …
A review on Single Image Super Resolution techniques using generative adversarial network
K Singla, R Pandey, U Ghanekar - Optik, 2022 - Elsevier
Abstract Single Image Super Resolution (SISR) is a process to obtain a high pixel density
and refined details from a low resolution (LR) image to get upscaled and sharper high …
and refined details from a low resolution (LR) image to get upscaled and sharper high …
Multi-scale attention generative adversarial network for medical image enhancement
High quality medical images are not only an important basis for doctors to carry out clinical
diagnosis and treatment, but also conducive to downstream tasks such as image analysis …
diagnosis and treatment, but also conducive to downstream tasks such as image analysis …
FS-GAN: Fuzzy Self-guided structure retention generative adversarial network for medical image enhancement
Improving the quality of medical images is helpful for doctors to perform clinical diagnosis
and treatment. Many medical image enhancement methods can achieve good performance …
and treatment. Many medical image enhancement methods can achieve good performance …