Search results
Results from the WOW.Com Content Network
In digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple image segments, also known as image regions or image objects (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to ...
U-Net was created by Olaf Ronneberger, Philipp Fischer, Thomas Brox in 2015 and reported in the paper "U-Net: Convolutional Networks for Biomedical Image Segmentation". [1] It is an improvement and development of FCN: Evan Shelhamer, Jonathan Long, Trevor Darrell (2014). "Fully convolutional networks for semantic segmentation". [2]
Microsoft Word - bases for segmentation.docx; Author: Home: Software used: PScript5.dll Version 5.2.2: File change date and time: 03:48, 30 November 2016: Date and time of digitizing: 03:48, 30 November 2016: Conversion program: Acrobat Distiller 10.1.10 (Windows) Encrypted: no: Page size: 612 x 792 pts (letter) Version of PDF format: 1.5
Text segmentation is the process of dividing written text into meaningful units, such as words, sentences, or topics. The term applies both to mental processes used by humans when reading text, and to artificial processes implemented in computers, which are the subject of natural language processing .
Sentence boundary disambiguation (SBD), also known as sentence breaking, sentence boundary detection, and sentence segmentation, is the problem in natural language processing of deciding where sentences begin and end.
Connected-component labeling (CCL), connected-component analysis (CCA), blob extraction, region labeling, blob discovery, or region extraction is an algorithmic application of graph theory, where subsets of connected components are uniquely labeled based on a given heuristic.
Bloody Mary Dip. Turn your favorite brunch cocktail into a creamy dip! It's zesty with just the right amount of heat. Top with chopped olives and serve with either veggies, crackers, or chips.
A one-dimension example of scale-space segmentation. A signal (black), multi-scale-smoothed versions of it (red), and segment averages (blue) based on scale-space segmentation The dendrogram corresponding to the segmentations in the figure above. Each "×" identifies the position of an extremum of the first derivative of one of 15 smoothed ...