Image classification based on the kohonen network and the data space modification Article Swipe
Volodymyr Gorokhovatskyi
,
Iryna Tvoroshenko
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.32782/cmis/2608-76
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.32782/cmis/2608-76
In this paper, we propose the solution of visual objects recognition in computer vision problems using the classification of descriptors of image keypoints based on the training of Kohonen neural network on the description data of etalon images.According to the results of training within the set of etalons, the image classification method has been improved by defining a specific data space in the form of a statistical center for each etalon.We propose mathematical models for the bitwise analysis of multiple descriptors searching for the centers and the method for convolution of descriptions from multiple descriptors with the determining a posteriori probabilities for the system of bit centers.Methods of data space transformation of description bits are proposed for various options for Kohonen network training, processing and estimation of class centers.The software implementation of the changed classifier was performed as well as the processing time with different options for determining the space of training data was estimated.Experimental researches confirmed the high efficiency of classification preserving sufficient performance and the ability to use proposed methods in real-time applications.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- http://doi.org/10.32782/cmis/2608-76
- https://doi.org/10.32782/cmis/2608-76
- OA Status
- gold
- Cited By
- 11
- References
- 33
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3027641041
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3027641041Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.32782/cmis/2608-76Digital Object Identifier
- Title
-
Image classification based on the kohonen network and the data space modificationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-01-01Full publication date if available
- Authors
-
Volodymyr Gorokhovatskyi, Iryna TvoroshenkoList of authors in order
- Landing page
-
https://doi.org/10.32782/cmis/2608-76Publisher landing page
- PDF URL
-
https://doi.org/10.32782/cmis/2608-76Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.32782/cmis/2608-76Direct OA link when available
- Concepts
-
Self-organizing map, Computer science, Space (punctuation), Pattern recognition (psychology), Artificial intelligence, Artificial neural network, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
11Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2, 2023: 4, 2021: 2, 2020: 3Per-year citation counts (last 5 years)
- References (count)
-
33Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3027641041 |
|---|---|
| doi | https://doi.org/10.32782/cmis/2608-76 |
| ids.doi | https://doi.org/10.32782/cmis/2608-76 |
| ids.mag | 3027641041 |
| ids.openalex | https://openalex.org/W3027641041 |
| fwci | 0.94470586 |
| type | article |
| title | Image classification based on the kohonen network and the data space modification |
| biblio.issue | |
| biblio.volume | 2608 |
| biblio.last_page | 1026 |
| biblio.first_page | 1013 |
| topics[0].id | https://openalex.org/T10627 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9933000206947327 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1707 |
| topics[0].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[0].display_name | Advanced Image and Video Retrieval Techniques |
| topics[1].id | https://openalex.org/T10057 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9868999719619751 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1707 |
| topics[1].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[1].display_name | Face and Expression Recognition |
| topics[2].id | https://openalex.org/T10824 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9860000014305115 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1707 |
| topics[2].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[2].display_name | Image Retrieval and Classification Techniques |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C111168008 |
| concepts[0].level | 3 |
| concepts[0].score | 0.8271129727363586 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1136838 |
| concepts[0].display_name | Self-organizing map |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.5607826113700867 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C2778572836 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5208797454833984 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q380933 |
| concepts[2].display_name | Space (punctuation) |
| concepts[3].id | https://openalex.org/C153180895 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5036253333091736 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q7148389 |
| concepts[3].display_name | Pattern recognition (psychology) |
| concepts[4].id | https://openalex.org/C154945302 |
| concepts[4].level | 1 |
| concepts[4].score | 0.47867971658706665 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[4].display_name | Artificial intelligence |
| concepts[5].id | https://openalex.org/C50644808 |
| concepts[5].level | 2 |
| concepts[5].score | 0.3048909306526184 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q192776 |
| concepts[5].display_name | Artificial neural network |
| concepts[6].id | https://openalex.org/C111919701 |
| concepts[6].level | 1 |
| concepts[6].score | 0.0 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q9135 |
| concepts[6].display_name | Operating system |
| keywords[0].id | https://openalex.org/keywords/self-organizing-map |
| keywords[0].score | 0.8271129727363586 |
| keywords[0].display_name | Self-organizing map |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.5607826113700867 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/space |
| keywords[2].score | 0.5208797454833984 |
| keywords[2].display_name | Space (punctuation) |
| keywords[3].id | https://openalex.org/keywords/pattern-recognition |
| keywords[3].score | 0.5036253333091736 |
| keywords[3].display_name | Pattern recognition (psychology) |
| keywords[4].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[4].score | 0.47867971658706665 |
| keywords[4].display_name | Artificial intelligence |
| keywords[5].id | https://openalex.org/keywords/artificial-neural-network |
| keywords[5].score | 0.3048909306526184 |
| keywords[5].display_name | Artificial neural network |
| language | en |
| locations[0].id | doi:10.32782/cmis/2608-76 |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | |
| locations[0].pdf_url | https://doi.org/10.32782/cmis/2608-76 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Computer Modeling and Intelligent Systems |
| locations[0].landing_page_url | http://doi.org/10.32782/cmis/2608-76 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5007841682 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-7839-6223 |
| authorships[0].author.display_name | Volodymyr Gorokhovatskyi |
| authorships[0].countries | UA |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I107158390 |
| authorships[0].affiliations[0].raw_affiliation_string | Kharkiv National University of Radio Electronics, Nauka Ave., 14, Kharkiv, 61166, Ukraine |
| authorships[0].institutions[0].id | https://openalex.org/I107158390 |
| authorships[0].institutions[0].ror | https://ror.org/01ctj1b90 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I107158390 |
| authorships[0].institutions[0].country_code | UA |
| authorships[0].institutions[0].display_name | Kharkiv National University of Radio Electronics |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Volodymyr Gorokhovatskyi |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Kharkiv National University of Radio Electronics, Nauka Ave., 14, Kharkiv, 61166, Ukraine |
| authorships[1].author.id | https://openalex.org/A5034631256 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-7184-8143 |
| authorships[1].author.display_name | Iryna Tvoroshenko |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | Iryna Tvoroshenko |
| authorships[1].is_corresponding | False |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.32782/cmis/2608-76 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Image classification based on the kohonen network and the data space modification |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10627 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9933000206947327 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1707 |
| primary_topic.subfield.display_name | Computer Vision and Pattern Recognition |
| primary_topic.display_name | Advanced Image and Video Retrieval Techniques |
| related_works | https://openalex.org/W2034551444, https://openalex.org/W2023416609, https://openalex.org/W1844640764, https://openalex.org/W2051216975, https://openalex.org/W2982550593, https://openalex.org/W2090505479, https://openalex.org/W2144077772, https://openalex.org/W2978573861, https://openalex.org/W2033914206, https://openalex.org/W2042327336 |
| cited_by_count | 11 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2023 |
| counts_by_year[1].cited_by_count | 4 |
| counts_by_year[2].year | 2021 |
| counts_by_year[2].cited_by_count | 2 |
| counts_by_year[3].year | 2020 |
| counts_by_year[3].cited_by_count | 3 |
| locations_count | 1 |
| best_oa_location.id | doi:10.32782/cmis/2608-76 |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://doi.org/10.32782/cmis/2608-76 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Computer Modeling and Intelligent Systems |
| best_oa_location.landing_page_url | http://doi.org/10.32782/cmis/2608-76 |
| primary_location.id | doi:10.32782/cmis/2608-76 |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | |
| primary_location.pdf_url | https://doi.org/10.32782/cmis/2608-76 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Computer Modeling and Intelligent Systems |
| primary_location.landing_page_url | http://doi.org/10.32782/cmis/2608-76 |
| publication_date | 2020-01-01 |
| publication_year | 2020 |
| referenced_works | https://openalex.org/W4256735985, https://openalex.org/W4242483532, https://openalex.org/W2901384204, https://openalex.org/W2895489375, https://openalex.org/W2117228865, https://openalex.org/W2141584146, https://openalex.org/W2963010714, https://openalex.org/W2907510400, https://openalex.org/W2994669088, https://openalex.org/W2728630881, https://openalex.org/W2182445001, https://openalex.org/W2546614363, https://openalex.org/W2963216120, https://openalex.org/W2593744649, https://openalex.org/W2963855133, https://openalex.org/W2906697496, https://openalex.org/W2954674884, https://openalex.org/W2518509711, https://openalex.org/W2903114830, https://openalex.org/W2948841488, https://openalex.org/W6631065984, https://openalex.org/W2993639591, https://openalex.org/W2994645333, https://openalex.org/W2989421085, https://openalex.org/W2587327040, https://openalex.org/W2963420272, https://openalex.org/W2963567641, https://openalex.org/W2606783869, https://openalex.org/W2797506598, https://openalex.org/W2885395180, https://openalex.org/W2810342222, https://openalex.org/W3036192984, https://openalex.org/W2964196326 |
| referenced_works_count | 33 |
| abstract_inverted_index.a | 57, 65, 98 |
| abstract_inverted_index.In | 0 |
| abstract_inverted_index.as | 137, 139 |
| abstract_inverted_index.by | 55 |
| abstract_inverted_index.in | 11, 61, 172 |
| abstract_inverted_index.of | 7, 18, 20, 27, 35, 41, 46, 64, 78, 90, 104, 107, 111, 126, 131, 150, 160 |
| abstract_inverted_index.on | 24, 31 |
| abstract_inverted_index.to | 38, 168 |
| abstract_inverted_index.we | 3 |
| abstract_inverted_index.and | 85, 124, 165 |
| abstract_inverted_index.are | 114 |
| abstract_inverted_index.bit | 105 |
| abstract_inverted_index.for | 68, 74, 82, 88, 101, 116, 119, 146 |
| abstract_inverted_index.has | 52 |
| abstract_inverted_index.set | 45 |
| abstract_inverted_index.the | 5, 16, 25, 32, 39, 44, 48, 62, 75, 83, 86, 96, 102, 132, 140, 148, 157, 166 |
| abstract_inverted_index.use | 169 |
| abstract_inverted_index.was | 135, 153 |
| abstract_inverted_index.been | 53 |
| abstract_inverted_index.bits | 113 |
| abstract_inverted_index.data | 34, 59, 108, 152 |
| abstract_inverted_index.each | 69 |
| abstract_inverted_index.form | 63 |
| abstract_inverted_index.from | 92 |
| abstract_inverted_index.high | 158 |
| abstract_inverted_index.this | 1 |
| abstract_inverted_index.time | 142 |
| abstract_inverted_index.well | 138 |
| abstract_inverted_index.with | 95, 143 |
| abstract_inverted_index.based | 23 |
| abstract_inverted_index.class | 127 |
| abstract_inverted_index.image | 21, 49 |
| abstract_inverted_index.space | 60, 109, 149 |
| abstract_inverted_index.using | 15 |
| abstract_inverted_index.center | 67 |
| abstract_inverted_index.etalon | 36 |
| abstract_inverted_index.method | 51, 87 |
| abstract_inverted_index.models | 73 |
| abstract_inverted_index.neural | 29 |
| abstract_inverted_index.paper, | 2 |
| abstract_inverted_index.system | 103 |
| abstract_inverted_index.vision | 13 |
| abstract_inverted_index.visual | 8 |
| abstract_inverted_index.within | 43 |
| abstract_inverted_index.Kohonen | 28, 120 |
| abstract_inverted_index.ability | 167 |
| abstract_inverted_index.bitwise | 76 |
| abstract_inverted_index.centers | 84 |
| abstract_inverted_index.changed | 133 |
| abstract_inverted_index.methods | 171 |
| abstract_inverted_index.network | 30, 121 |
| abstract_inverted_index.objects | 9 |
| abstract_inverted_index.options | 118, 145 |
| abstract_inverted_index.propose | 4, 71 |
| abstract_inverted_index.results | 40 |
| abstract_inverted_index.various | 117 |
| abstract_inverted_index.analysis | 77 |
| abstract_inverted_index.computer | 12 |
| abstract_inverted_index.defining | 56 |
| abstract_inverted_index.etalons, | 47 |
| abstract_inverted_index.improved | 54 |
| abstract_inverted_index.multiple | 79, 93 |
| abstract_inverted_index.problems | 14 |
| abstract_inverted_index.proposed | 115, 170 |
| abstract_inverted_index.software | 129 |
| abstract_inverted_index.solution | 6 |
| abstract_inverted_index.specific | 58 |
| abstract_inverted_index.training | 26, 42, 151 |
| abstract_inverted_index.confirmed | 156 |
| abstract_inverted_index.different | 144 |
| abstract_inverted_index.etalon.We | 70 |
| abstract_inverted_index.keypoints | 22 |
| abstract_inverted_index.performed | 136 |
| abstract_inverted_index.real-time | 173 |
| abstract_inverted_index.searching | 81 |
| abstract_inverted_index.training, | 122 |
| abstract_inverted_index.classifier | 134 |
| abstract_inverted_index.efficiency | 159 |
| abstract_inverted_index.estimation | 125 |
| abstract_inverted_index.posteriori | 99 |
| abstract_inverted_index.preserving | 162 |
| abstract_inverted_index.processing | 123, 141 |
| abstract_inverted_index.researches | 155 |
| abstract_inverted_index.sufficient | 163 |
| abstract_inverted_index.centers.The | 128 |
| abstract_inverted_index.convolution | 89 |
| abstract_inverted_index.description | 33, 112 |
| abstract_inverted_index.descriptors | 19, 80, 94 |
| abstract_inverted_index.determining | 97, 147 |
| abstract_inverted_index.performance | 164 |
| abstract_inverted_index.recognition | 10 |
| abstract_inverted_index.statistical | 66 |
| abstract_inverted_index.descriptions | 91 |
| abstract_inverted_index.mathematical | 72 |
| abstract_inverted_index.applications. | 174 |
| abstract_inverted_index.probabilities | 100 |
| abstract_inverted_index.classification | 17, 50, 161 |
| abstract_inverted_index.implementation | 130 |
| abstract_inverted_index.transformation | 110 |
| abstract_inverted_index.centers.Methods | 106 |
| abstract_inverted_index.images.According | 37 |
| abstract_inverted_index.estimated.Experimental | 154 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 93 |
| corresponding_author_ids | https://openalex.org/A5007841682 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I107158390 |
| citation_normalized_percentile.value | 0.76634505 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |