The image thresholding methods consume a lot of time due to computational complexity
when the number of threshold levels increases. In order to reduce computation time and …

Due to technical advancements and the proliferation of mobile applications, facial analysis
(FA) of humans has recently become an important area for computer vision research. FA …

With the development and wider application of meta-heuristic optimization algorithms,
researchers increasingly apply them to threshold optimization of multi-level image …

K-means clustering is known to be the most traditional approach in machine learning. It's
been put to a lot of different uses. However, it has difficulty with initialization and performs …

The distribution characteristic of populations is one of the main characteristics of population.
The pattern of distribution characteristics determines the probability law of individual values …

From the end of 2019 until now, the Coronavirus Disease 2019 (COVID-19) has been
rampaging around the world, posing a great threat to people's lives and health, as well as a …

In this study, we apply multilevel thresholding segmentation to color images of plant disease.
Given that thresholding segmentation is just an optimization problem, we use Otsu's function …

An automatic thresholding method based on Shannon entropy difference and dynamic
synergic entropy is proposed to select a reasonable threshold from the gray level image with …

Influenza epidemic is a serious threat to the entire world, which causes thousands of death
every year and can be considered as a public health emergency that needs to be more …

Regardless of public perceptions of the agricultural techniques, the fact is that the current
agriculture industry is more data-driven, accurate, and intelligent than before. Therefore …