Automatic Classification of Optical Defects of Mirrors from Ronchigram Images Using Bag of Visual Words and Support Vector Machines

2018 ◽  
pp. 719-726
Author(s):  
Daniel Zapata ◽  
Angel Cruz-Roa ◽  
Andrés Jiménez
Keyword(s):  
Support Vector Machines ◽  
Automatic Classification ◽  
Support Vector ◽  
Bag Of Visual Words ◽  
Visual Words ◽  
Vector Machines

scholarly journals The Pattern Recognition in Cattle Brand using Bag of Visual Words and Support Vector Machines Multi-Class

2018 ◽  
Vol 21 (61) ◽  
pp. 1
Author(s):  
Carlos Silva ◽  
Daniel Welfer ◽  
Cláudia Dornelles
Keyword(s):  
Support Vector Machines ◽  
Processing Time ◽  
Support Vector ◽  
Bag Of Visual Words ◽  
Visual Words ◽  
City Hall ◽  
Points Of Interest ◽  
Image Characteristics ◽  
Vector Machines ◽  
Results Reporting

The recognition images of cattle brand in an automatic way is a necessity to governmental organs responsible for this activity. To help this process, this work presents a method that consists in using Bag of Visual Words for extracting of characteristics from images of cattle brand and Support Vector Machines Multi-Class for classification. This method consists of six stages: a) select database of images; b) extract points of interest (SURF); c) create vocabulary (K-means); d) create vector of image characteristics (visual words); e) train and sort images (SVM); f) evaluate the classification results. The accuracy of the method was tested on database of municipal city hall, where it achieved satisfactory results, reporting 86.02% of accuracy and 56.705 seconds of processing time, respectively.

scholarly journals Classification of hyperspectral endocrine tissue images using support vector machines

2020 ◽  
Vol 16 (5) ◽  
pp. 1-10
Author(s):  
Marianne Maktabi ◽  
Hannes Köhler ◽  
Magarita Ivanova ◽  
Thomas Neumuth ◽  
Nada Rayes ◽  
...  
Keyword(s):  
Support Vector Machines ◽  
Support Vector ◽  
Endocrine Tissue ◽  
Vector Machines
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