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 …

A Review of Biosensors and Artificial Intelligence in Healthcare and Their Clinical Significance

Y Hayat, M Tariq, A Hussain, A Tariq… - … Research Journal of …, 2024 - irjems.org
In the past decade, a substantial increase in medical data from various sources, including
wearable sensors, medical imaging, personal health records, and public health …

[HTML][HTML] Swin transformer for fast MRI

J Huang, Y Fang, Y Wu, H Wu, Z Gao, Y Li, J Del Ser… - Neurocomputing, 2022 - Elsevier
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 …

[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 …

Hqg-net: Unpaired medical image enhancement with high-quality guidance

C He, K Li, G Xu, J Yan, L Tang… - … on Neural Networks …, 2023 - ieeexplore.ieee.org
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 …

Artificial intelligence and biosensors in healthcare and its clinical relevance: A review

R Qureshi, M Irfan, H Ali, A Khan, AS Nittala, S Ali… - IEEE …, 2023 - ieeexplore.ieee.org
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 …

Rformer: Transformer-based generative adversarial network for real fundus image restoration on a new clinical benchmark

Z Deng, Y Cai, L Chen, Z Gong, Q Bao… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Ophthalmologists have used fundus images to screen and diagnose eye diseases.
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 …

Multi-scale attention generative adversarial network for medical image enhancement

G Zhong, W Ding, L Chen, Y Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …

FS-GAN: Fuzzy Self-guided structure retention generative adversarial network for medical image enhancement

YF Yu, G Zhong, Y Zhou, L Chen - Information Sciences, 2023 - Elsevier
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 …