Examination and Issues of Kumamoto Castle Ishigaki Region Extraction Focusing on Stone Contour Features

2020 ◽  
pp. 43-53
Author(s):  
Yuuki Yamasaki ◽  
Masahiro Migita ◽  
Go Koutaki ◽  
Masashi Toda ◽  
Tsuyoshi Kishigami
Keyword(s):  
Region Extraction

Intelligent system of English composition scoring model based on improved machine learning algorithm

2020 ◽  
pp. 1-11
Author(s):  
Jie Liu ◽  
Lin Lin ◽  
Xiufang Liang
Keyword(s):  
Machine Learning ◽  
Evaluation System ◽  
Intelligent System ◽  
Learning Algorithm ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Assessment System ◽  
English Composition ◽  
Region Extraction ◽  
Constraint Model

The online English teaching system has certain requirements for the intelligent scoring system, and the most difficult stage of intelligent scoring in the English test is to score the English composition through the intelligent model. In order to improve the intelligence of English composition scoring, based on machine learning algorithms, this study combines intelligent image recognition technology to improve machine learning algorithms, and proposes an improved MSER-based character candidate region extraction algorithm and a convolutional neural network-based pseudo-character region filtering algorithm. In addition, in order to verify whether the algorithm model proposed in this paper meets the requirements of the group text, that is, to verify the feasibility of the algorithm, the performance of the model proposed in this study is analyzed through design experiments. Moreover, the basic conditions for composition scoring are input into the model as a constraint model. The research results show that the algorithm proposed in this paper has a certain practical effect, and it can be applied to the English assessment system and the online assessment system of the homework evaluation system algorithm system.

Fast reconstruction of fluorescence molecular tomography via a permissible region extraction strategy

2014 ◽  
Vol 31 (8) ◽  
pp. 1886 ◽  
Author(s):  
Jiulou Zhang ◽  
Junwei Shi ◽  
Xu Cao ◽  
Fei Liu ◽  
Jing Bai ◽  
...  
Keyword(s):  
Fluorescence Molecular Tomography ◽  
Region Extraction ◽  
Fast Reconstruction

Palm region extraction for contactless palmprint recognition

2015 ◽  
Author(s):  
Koichi Ito ◽  
Takuto Sato ◽  
Shoichiro Aoyama ◽  
Shuji Sakai ◽  
Shusaku Yusa ◽  
...  
Keyword(s):  
Palmprint Recognition ◽  
Region Extraction

EXTRACTION OF BIBLIOGRAPHY INFORMATION BASED ON IMAGE OF BOOK COVER

2000 ◽  
Vol 14 (07) ◽  
pp. 963-978 ◽  
Author(s):  
HUA YANG ◽  
MASAAKI KASHIMURA ◽  
NORIKADU ONDA ◽  
SHINJI OZAWA
Keyword(s):  
Color Image ◽  
Color Space ◽  
Input Image ◽  
Color Image Processing ◽  
Front Cover ◽  
Stroke Width ◽  
Other Information ◽  
Region Extraction ◽  
Hsi Color Space ◽  
Rgb Color Space

This paper describes a new system for extracting and classifying bibliography regions from the color image of a book cover. The system consists of three major components: preprocessing, color space segmentation and text region extraction and classification. Preprocessing extracts the edge lines of the book and geometrically corrects and segments the input image, into the parts of front cover, spine and back cover. The same as all color image processing researches, the segmentation of color space is an essential and important step here. Instead of RGB color space, HSI color space is used in this system. The color space is segmented into achromatic and chromatic regions first; and both the achromatic and chromatic regions are segmented further to complete the color space segmentation. Then text region extraction and classification follow. After detecting fundamental features (stroke width and local label width) text regions are determined. By comparing the text regions on front cover with those on spine, all extracted text regions are classified into suitable bibliography categories: author, title, publisher and other information, without applying OCR.

Semi-automatic brain region extraction (SABRE) reveals superior cortical and deep gray matter atrophy in MS

NeuroImage ◽  
2006 ◽  
Vol 29 (2) ◽  
pp. 505-514 ◽  
Author(s):  
D.A. Carone ◽  
R.H.B. Benedict ◽  
M.G. Dwyer ◽  
D.L. Cookfair ◽  
B. Srinivasaraghavan ◽  
...  
Keyword(s):  
Gray Matter ◽  
Brain Region ◽  
Gray Matter Atrophy ◽  
Region Extraction ◽  
Deep Gray Matter

Semiautomatic brain region extraction: a method of parcellating brain regions from structural magnetic resonance images

NeuroImage ◽  
2004 ◽  
Vol 22 (4) ◽  
pp. 1492-1502 ◽  
Author(s):  
L.A Dade ◽  
F.Q Gao ◽  
N Kovacevic ◽  
P Roy ◽  
C Rockel ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Brain Region ◽  
Brain Regions ◽  
Magnetic Resonance Images ◽  
Region Extraction

A permissible region extraction based on a knowledge priori for X-ray luminescence computed tomography

2017 ◽  
Vol 25 (2) ◽  
pp. 147-154 ◽  
Author(s):  
Huangjian Yi ◽  
Xuan Qu ◽  
Yi Sun ◽  
Jinye Peng ◽  
Yuqing Hou ◽  
...  
Keyword(s):  
Computed Tomography ◽  
X Ray ◽  
Region Extraction
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