Current deep learning-based texture recognition methods extract spatial orderless features
from pre-trained deep learning models that are trained on large-scale image datasets …

Understanding and controlling the self-assembly of vertically oriented carbon nanotube
(CNT) forests is essential for realizing their potential in myriad applications. The governing …

This research paper introduces the novel local binary pattern (LBP) variant for face
recognition (FR) called as neighborhood and center difference-based-LBP (NCDB-LBP). In …

As one of the most successful local feature descriptors, the local binary pattern (LBP)
estimates the texture distribution rule of an image based on the signs of differences between …

Local binary pattern (LBP) and its variants have been successfully applied in texture feature
extraction. However, it is hard for most LBP-based methods to effectively describe and …

Convolutional neural networks have shown successful results in image classification
achieving real-time results superior to the human level. However, texture images still pose …

Despite the remarkable progress that has been made to reduce global malaria mortality by
29% in the past 5 years, malaria is still a serious global health problem. Inadequate …

Texture is an important characteristic for different computer vision tasks and applications.
Local binary pattern (LBP) is considered one of the most efficient texture descriptors yet …

The muscular dystrophies are made up of a diverse group of rare genetic diseases
characterized by progressive loss of muscle strength and muscle damage. Since there is no …

This paper presents a simple, efficient, yet robust approach, named joint-scale local binary
pattern (JLBP), for texture classification. In the proposed approach, the joint-scale strategy is …