Segmentation of satellite images is the noteworthy and essential step for better
understanding and analysis in various applications such as disaster and crisis management …

In this paper, a novel satellite image segmentation technique based on dynamic Harris
hawks optimization with a mutation mechanism (DHHO/M) is proposed. Compared with the …

Multilevel-thresholding is an efficient method used in image segmentation. This paper
presents a hybrid meta-heuristic approach for multi-level thresholding image segmentation …

Convolutional neural networks (CNN) are deep learning models widely reported as
performing well in several image classification tasks. Training the networks for optimal …

The use of binary decision diagrams (BDDs) has proliferated in numerous fields. When a
system criterion is formulated in form of a Boolean function, its BDD is constructed. Each …

Color image segmentation is the primary step to elicit detailed information of the image with
RGB color space. The key to acquire the region of interest is the straightforward, instinctual …

Multilevel thresholding image segmentation has received considerable attention in several
image processing applications. However, the process of determining the optimal threshold …

Maize is a major global food crop and as one of the most productive grain crops, it can be
eaten; it is also a good feed for the development of animal husbandry and essential raw …

A vehicle cruise control (VCC) system is one of the real-world engineering optimization
problems gaining a considerable attention because of the concerns related to safety and …

Multilevel thresholding is one of the most commonly used methods in image segmentation.
However, the exhaustive search method is computationally expensive for selecting the …