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 …
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
The concept of intelligent visual identification of abnormal human activity has raised the
standards of surveillance systems, situation cognizance, homeland safety and smart …
standards of surveillance systems, situation cognizance, homeland safety and smart …
Genetic algorithm based adaptive histogram equalization (GAAHE) technique for medical image enhancement
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 …
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
Early identification of melanocytic skin lesions increases the survival rate for skin cancer
patients. Automated melanocytic skin lesion extraction from dermoscopic images using the …
patients. Automated melanocytic skin lesion extraction from dermoscopic images using the …
[PDF][PDF] Fruit Image Classification Using Deep Learning.
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 …
Many deep learning-based procedures worked out so far to classify images may have some …
Fuzzy-contextual contrast enhancement
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 …
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 …
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 …
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 …
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
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 …
findings of chest radiography play a key role in the diagnosis, management, and follow-up of …