Lung cancer is one of the most dangerous diseases that cause a large number of deaths. Early detection and analysis can be very helpful for successful treatment. Image segmentation plays a key role in the early detection and diagnosis of lung cancer. K-means algorithm and classic PSO clustering are the most common methods for segmentation that have poor outputs. In t...

Automatic road extraction from aerial images can be very helpful in traffic control and vehicle guidance systems. Most of the road detection approaches are based on image segmentation algorithms. Color-based segmentation is very sensitive to light changes and consequently the change of weather condition affects the recognition rate of road detection systems. In order to reduce the light change ...

Semi-supervised video object segmentation is a task of propagating instance masks given in the first frame to entire video. It challenging since it usually suffers from heavy occlusions, large deformation, and variations objects. To alleviate these problems, many existing works apply time-consuming techniques such as fine-tuning, post-processing, or extracting optical flow, which makes them int...

In statistical machine translation (SMT), word segmentation is generally a necessary step for languages that do not naturally delimit words. For many low-resource languages there are no word segmentation tools, and research on word segmentation for these languages is often quite scarce. In this paper, we study several plausible methods for Myanmar word segmentation for machine translation in or...

the purpose of was segmentation of customers according to benefit sought. market segmentation is viewing a heterogeneous market as a number of smaller homogeneous markets, in response to differing preferences, attributable to the desires of customers for more precise satisfaction of their varying wants. the data analysis was based on questionnaires which had been gathered from three metropolise...