This project segments 9,999 high-value retail customers using RFM (Recency, Frequency, Monetary) methodology. The analysis identifies distinct customer groups and provides targeted business ...

1 School of Science, Tianjin University of Technology and Education, Tianjin, China. 2 School of Big Data, Lvliang Vocational and Technical College, Lvliang, China. Early image segmentation was mainly ...

No matter what type(s) of photography you like to pursue, mastering exposure is key to creating successful images. While it can be tempting to use your camera's screen to judge exposure, that display ...

For startups and established businesses, understanding the importance of segmentation is essential for the granular analysis of consumer demographics, behaviors, needs, and preferences. These insights ...

Abstract: Brain malignant growth detection is eased using medical images and machine learning paradigms. This article introduces a differential region-based segmentation method to improve brain tumor ...

Michael Lieberman presents a classic Saturday challenge. By Caitlin Lovinger SATURDAY PUZZLE — Michael Lieberman’s first New York Times crossword was a bit over four years ago, and he has become a ...

Abstract: This study introduces a method for material classification using transient histograms obtained via a single-photon avalanche diode (SPAD) sensor. Temporal resolution in optical sensing plays ...

Accurate brain tumour segmentation is critical for diagnosis and treatment planning, yet challenging due to tumour complexity. Manual segmentation is time-consuming and variable, necessitating ...

This toolbox implements the algorithm described in J.Gilles, K.Heal, "A parameterless scale-space approach to find meaningful modes in histograms - Application to image and spectrum segmentation".

The manuscript introduces an important and innovative non-AI computational method for segmenting noisy grayscale images, with a particular focus on identifying immunostained potassium ion channel ...