Semantic content analysis and annotation of histological images
F Yu, HHS Ip - Computers in Biology and Medicine, 2008 - Elsevier
This paper presents a novel two-dimensional (2-D) stochastic method for semantic analysis
of the content of histological images Specifically, we propose a 2-D generalization of the …
of the content of histological images Specifically, we propose a 2-D generalization of the …
Prediction of power system security levels
SS Halilcevic, F Gubina… - IEEE Transactions on …, 2009 - ieeexplore.ieee.org
In the paper, Markov chains in conjunction with Monte Carlo simulation are used to predict
the power system security level. The new approach uses a Markov chain for each identified …
the power system security level. The new approach uses a Markov chain for each identified …
Article segmentation in digitised newspapers with a 2d markov model
Document analysis and recognition is increasingly used to digitise collections of historical
books, newspapers and other periodicals. In the digital humanities, it is often the goal to …
books, newspapers and other periodicals. In the digital humanities, it is often the goal to …
Image classification algorithm based on stacked sparse coding deep learning model-optimized kernel function nonnegative sparse representation
F An - Soft Computing, 2020 - Springer
Image classification has received extensive attention as an important technical means of
acquiring image information. It has been widely used in various engineering fields. Although …
acquiring image information. It has been widely used in various engineering fields. Although …
A new method for image classification by using multilevel association rules
VS Tseng, MH Wang, JH Su - 21st International Conference on …, 2005 - ieeexplore.ieee.org
With the popularity of multimedia applications, the huge amount of image and video related
to real life have led to the proliferation of emerging storage techniques. Contented-based …
to real life have led to the proliferation of emerging storage techniques. Contented-based …
Chart image understanding and numerical data extraction
A Mishchenko, N Vassilieva - 2011 Sixth International …, 2011 - ieeexplore.ieee.org
Chart images in digital documents are an important source of valuable information that is
largely under-utilized for data indexing and information extraction purposes. We developed …
largely under-utilized for data indexing and information extraction purposes. We developed …
Image classification with kernelized spatial-context
The goal of image classification is to classify a collection of unlabeled images into a set of
semantic classes. Many methods have been proposed to approach this goal by leveraging …
semantic classes. Many methods have been proposed to approach this goal by leveraging …
Enhanced hidden markov models for accelerating medical volumes segmentation
A fully automated unsupervised image segmentation method using Hidden Markov Models
(HMMs) is proposed to segment medical volumes. The application of this system to medical …
(HMMs) is proposed to segment medical volumes. The application of this system to medical …
The reading of components of diabetic retinopathy: an evolutionary approach for filtering normal digital fundus imaging in screening and population based studies
In any diabetic retinopathy screening program, about two-thirds of patients have no
retinopathy. However, on average, it takes a human expert about one and a half times …
retinopathy. However, on average, it takes a human expert about one and a half times …
Hierarchical conditional random fields for web extraction
A method and system for labeling object information of an information page is provided. A
labeling system identifies an object record of an information page based on the labeling of …
labeling system identifies an object record of an information page based on the labeling of …