An experiment-based review of low-light image enhancement methods

W Wang, X Wu, X Yuan, Z Gao - Ieee Access, 2020 - ieeexplore.ieee.org
Images captured under poor illumination conditions often exhibit characteristics such as low
brightness, low contrast, a narrow gray range, and color distortion, as well as considerable …

A review of state-of-the-art techniques for abnormal human activity recognition

C Dhiman, DK Vishwakarma - Engineering Applications of Artificial …, 2019 - Elsevier
The concept of intelligent visual identification of abnormal human activity has raised the
standards of surveillance systems, situation cognizance, homeland safety and smart …

Genetic algorithm based adaptive histogram equalization (GAAHE) technique for medical image enhancement

UK Acharya, S Kumar - Optik, 2021 - Elsevier
Abstract In Magnetic Resonance Imaging (MRI), the poor quality images may not provide the
sufficient information for the visual interpretation of the affected locations of human body. So …

Skin lesion extraction using multiscale morphological local variance reconstruction based watershed transform and fast fuzzy C-means clustering

R Rout, P Parida, Y Alotaibi, S Alghamdi, OI Khalaf - Symmetry, 2021 - mdpi.com
Early identification of melanocytic skin lesions increases the survival rate for skin cancer
patients. Automated melanocytic skin lesion extraction from dermoscopic images using the …

[PDF][PDF] Fruit Image Classification Using Deep Learning.

HS Gill, OI Khalaf, Y Alotaibi… - … , Materials & Continua, 2022 - cdn.techscience.cn
Fruit classification is found to be one of the rising fields in computer and machine vision.
Many deep learning-based procedures worked out so far to classify images may have some …

Fuzzy-contextual contrast enhancement

AS Parihar, OP Verma, C Khanna - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
This paper presents contrast enhancement algorithms based on fuzzy contextual information
of the images. We introduce fuzzy similarity index and fuzzy contrast factor to capture the …

[HTML][HTML] Unsupervised ship detection in SAR imagery based on energy density-induced clustering

Z Yuan, Y Li, Y Liu, J Liang, Y Zhang - International Journal of Network …, 2023 - sciltp.com
Intelligent recognition of maritime ship targets from synthetic aperture radar (SAR) imagery is
a hot research issue. However, interferences such as the strong sea clutter, sidelobe, small …

An image enhancement algorithm to improve road tunnel crack transfer detection

J Liu, Z Zhao, C Lv, Y Ding, H Chang, Q **e - Construction and Building …, 2022 - Elsevier
Cracks are a common disease in road transportation infrastructure, while crack detection
has been a difficult task for a long time, especially for tunnels. Both training data and network …

Real-time robust detector for underwater live crabs based on deep learning

S Cao, D Zhao, X Liu, Y Sun - Computers and Electronics in Agriculture, 2020 - Elsevier
Image analysis technology has drawn dramatic attention and developed rapidly because it
enables a non-extractive and non-destructive approach to data acquisition of crab …

Deep learning, reusable and problem-based architectures for detection of consolidation on chest X-ray images

H Behzadi-Khormouji, H Rostami, S Salehi… - Computer methods and …, 2020 - Elsevier
Background and objective In most patients presenting with respiratory symptoms, the
findings of chest radiography play a key role in the diagnosis, management, and follow-up of …