Segmentation of organisational segments of the brain is the essential problem in medical image investigation. This paper reviews several existing brain tumor segmentation and detection methodology for MRI of brain image. Altogether the phases for detecting brain tumor have been discussed comprising preprocessing steps. Pre-processing involves several operations like non local, diagnostic correc...

Page segmentation and classification are important parts of the document analysis process. The aim is to extract and classify different parts of the page. This paper proposes an approach in which these two phases are combined. The integration process includes fast feature extraction with rule-based classification and label propagation using connectivity analysis providing classified areas in th...

Semantic segmentation is the task of clustering together parts an image that belong to same object class. webpages important for inferring contextual information from webpage. This study examines and compares deep learning methods classifying based on imagery obscured by semantic segmentation. Fully convolutional neural network architectures (UNet FCN-8) with defined hyperparameters loss functi...

Research in the Computer Vision Laboratory at the University of Maryland covers a broad range of topics and applications related to visual processing. This paper highlights some recent and ongoing research in the area of Document Understanding. The topics addressed include page segmentation, page decomposition, stroke interpretation , logo recognition, forms processing and the generation of syn...

It is well known that some XML elements correspond to objects (in the sense of object-orientation) and others do not. The question we consider in this paper is what benefits we can derive from paying attention to such object semantics, particularly for the problem of keyword queries. Keyword queries against XML data have been studied extensively in recent years, with several lowest-common-ances...

The extraction of the main content web pages is widely used in search engines, but a lot irrelevant information, such as advertisements, navigation, and junk included pages. Such information reduces efficiency processing content-based applications. This study aimed to extract using DOM Tree rationality segmentation results based on entropy nodes from Tree. first step this research was classify ...

One fundamental difficulty with evaluation of segmentation is that there is no objective, clear definition of good or bad segmentation. Even worse, different observers often do not agree on how to segment the same image. In this paper, we present six unsupervised metrics in the literature that are commonly used to evaluate segmentation results. Then we propose a framework to find the best compa...