Recognition and classification problems with standard training information

Zhuravlev, Yu. I.; Zenkin, A. A.; Zenkin, A.I.; Isaev, Igor; Koltsov, P. P.; Kochetkov, Denis; Ryazanov, Vladimir

doi:10.1016/0041-5553(80)90096-8

Cited by 4 publications

(4 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our case, binarization was carried out by the threshold method, with the optimization of its choice [3][4][5]. Then the noise was removed from the image [5][6]. Segmentation was performed automatically.…”

Section: Methodological Problems Of Binarizationmentioning

confidence: 99%

“…The considered post-projection task with the help of the statistical classification apparatus assumes that k parameters Thus, from the general amount of questions solved at statistical classification it is necessary to allocate two basic questions: quantitative estimation of training to extrapolation connections and formation of optimum recognition model [6].…”

Section: Prediction As Pattern Recognition (One-dimensional Case)mentioning

confidence: 99%

“…For problems close in complexity to the problem of written signs recognition, when the nature of the source is absolutely unclear, and the seemingly obvious possibilities of solving in an incomprehensible way turn out to be insolvent, one of the best is the possibility of cascading solution. [4][5][6]. In this case, dividing an initial problem into a series of essentially simpler subtasks within the framework of the supposed model of the situation generating the problem being solved, one can count on success by a sequence of local but mutually agreed solutions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Probably-Statistical Method for Written Signs Recognition Using the Measure of Proximity

et al. 2020

View full text Add to dashboard Cite

The paper describes ways to recognize written signs when the nature of the source is absolutely unclear and the seemingly obvious possibilities for solving the problem are not clear as well. The article deals with methods of recognition of binary images in order to compare them and highlight the best. The images of documents are obtained with the help of a camera. The quality is low. The images of the collection were segmented and passed binaryization. A control sample was selected to test the recognition methods from the resulting collection. The paper describes the method of comparing images, their advantages and disadvantages when recognizing handwritten shorthand characters. The results obtained by comparing the characters of the control sample allowed determining the best method “method of comparison of forms”.

show abstract

Section: Methodological Problems Of Binarizationmentioning

confidence: 99%

Section: Prediction As Pattern Recognition (One-dimensional Case)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Probably-Statistical Method for Written Signs Recognition Using the Measure of Proximity

et al. 2020

View full text Add to dashboard Cite

show abstract

“…This is why we applied our classification method, based on the so-called test approach. (Juravlev [1] and Kudriavtzev are considered to be the pioneers of this approach, further refined in specific directions [2], [3]). The main advantage of the method in our case is that it is possible to obtain objective and reliable results by using relatively small subsets of patterns, in any case even below 10.…”

mentioning

confidence: 99%

Application of Classification Methods to a Problem Related to Specific Groups of E-Government Users

Angelova¹,

Eskenazi²

2008

SJC

View full text Add to dashboard Cite

One of the important tasks of the EU ELOST project on E-government and Low Socio-Economic Status Groups (LSG) was to compare experts’ opinions on fundamental problems of the subject. This papers shows how the application of specific classification methods to experts’ formalized answers could lead to some non-trivial and objective conclusions about interdependencies and the interrelation between e-government policies/tools and experts’ background and country affiliation.

show abstract