It is estimated that 80% of crashes and 65% of near collisions involved drivers inattentive to
traffic for three seconds before the event. This paper develops an algorithm for extracting …

In this paper, a new computation for gray level co-occurrence matrix (GLCM) is proposed.
The aim is to reduce the computation burden of the original GLCM computation. The …

Image processing and machine learning technique are modified to use the quality grading of
soybean seeds. Due to quality grading is a very important process for the soybean industry …

The use of a graphics processing unit (GPU) together with a CPU, referred as GPU-
accelerated computing, to accelerate tasks that requires extensive computations has been …

Classifying urban land cover from high-resolution satellite imagery is challenging, and those
challenges are compounded when the imagery databases are very large. Accurate land …

Pattern classification applications can be found everywhere, especially the ones that use
computer vision. What makes them difficult to embed is the fact that they often require a lot of …

In biological applications, features are extracted from microscopy images of cells and are
used for automated classification. Usually, a huge number of images has to be analyzed so …

This paper presents a novel and optimized embedded architecture based FPGA for an
efficient and fast computation of grey level co-occurrence matrices (GLCM) and Haralick …

Process migration is essential for runtime load balancing. In Grid and shared networked
environments, load imbalance is not only caused by the dynamic nature of underlying …

The study introduces a new quantitative precipitation estimation (QPE) algorithm from
Advanced Baseline Imager (ABI) observations from GOES‐16 across the contiguous USA …