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 ...

All television shows must come to an end — except, perhaps, "The Simpsons," which completed its 36th season in 2025 with no end in sight. But studios, lured by the promise of a built-in audience, have ...

Abstract: This paper proposed an auto-adaptive threshold method of two-dimensional (2-D) histogram based on multi-resolution analysis (MRA), decreasing the calculation complexity of 2-D histogram ...

Instance segmentation has been the most challenging task in the field of computer vision, and its techniques are widely used in the fields of intelligent driving, intelligent medical imaging, remote ...

Python implementation of the adaptive seed (centroid) placement part in Adaptive-SNIC algorithm. Following figure shows the corresponding seeds produced by Adaptive-SNIC algorithm. It is clear that ...

Objectives: Oral cavity-derived cancer pathological images (OPI) are crucial for diagnosing oral squamous cell carcinoma (OSCC), but existing deep learning methods for OPI segmentation rely heavily on ...

I am trying to use this #4361 feature and not being able to get the desired output. a = meter.create_histogram('a_latency', explicit_bucket_boundaries_advisory=[0.0, 1.0, 2.0]) a.record(99.9) I am ...