Color Detection using Deep Learning Techniques Article Swipe
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.55248/gengpi.5.0524.1358
This abstract provides a concise overview of utilizing deep learning in tandem with OpenCV, Pillow, and clustering techniques for robust color detection.It discusses the integration of deep learning frameworks with OpenCV and Pillow libraries, emphasizing the role of clustering algorithms for color quantization and segmentation.Implementation details, evaluation metrics, and future research directions are also briefly addressed, highlighting the potential for advancements in real-world color detection applications.The methodology involves employing clustering algorithms to analyse image data and extract dominant color information.This project promises to be an illuminating journey, where we'll witness the power of technology in understanding and interpreting the colourful world.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- http://doi.org/10.55248/gengpi.5.0524.1358
- https://doi.org/10.55248/gengpi.5.0524.1358
- OA Status
- bronze
- Cited By
- 1
- References
- 7
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399460025
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4399460025Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.55248/gengpi.5.0524.1358Digital Object Identifier
- Title
-
Color Detection using Deep Learning TechniquesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-05-17Full publication date if available
- Authors
-
Jalappagari Sainath, M. S. Shankar Reddy, Siva Saketh, Ch. Sakshitha, K. Akshay, Thayyaba Khatoon Mohammed, Prof.A. kalyaniList of authors in order
- Landing page
-
https://doi.org/10.55248/gengpi.5.0524.1358Publisher landing page
- PDF URL
-
https://doi.org/10.55248/gengpi.5.0524.1358Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.55248/gengpi.5.0524.1358Direct OA link when available
- Concepts
-
Artificial intelligence, Computer science, Deep learning, Computer vision, Pattern recognition (psychology)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1Per-year citation counts (last 5 years)
- References (count)
-
7Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4399460025 |
|---|---|
| doi | https://doi.org/10.55248/gengpi.5.0524.1358 |
| ids.doi | https://doi.org/10.55248/gengpi.5.0524.1358 |
| ids.openalex | https://openalex.org/W4399460025 |
| fwci | 0.53015756 |
| type | article |
| title | Color Detection using Deep Learning Techniques |
| biblio.issue | 5 |
| biblio.volume | 5 |
| biblio.last_page | 9532 |
| biblio.first_page | 9529 |
| topics[0].id | https://openalex.org/T10824 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9833999872207642 |
| 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 | Image Retrieval and Classification Techniques |
| topics[1].id | https://openalex.org/T10689 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9786999821662903 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2214 |
| topics[1].subfield.display_name | Media Technology |
| topics[1].display_name | Remote-Sensing Image Classification |
| topics[2].id | https://openalex.org/T10627 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9555000066757202 |
| 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 | Advanced Image and Video Retrieval Techniques |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C154945302 |
| concepts[0].level | 1 |
| concepts[0].score | 0.5905078053474426 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[0].display_name | Artificial intelligence |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.551028311252594 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C108583219 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5015552043914795 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q197536 |
| concepts[2].display_name | Deep learning |
| concepts[3].id | https://openalex.org/C31972630 |
| concepts[3].level | 1 |
| concepts[3].score | 0.3521338999271393 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[3].display_name | Computer vision |
| concepts[4].id | https://openalex.org/C153180895 |
| concepts[4].level | 2 |
| concepts[4].score | 0.34986740350723267 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q7148389 |
| concepts[4].display_name | Pattern recognition (psychology) |
| keywords[0].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[0].score | 0.5905078053474426 |
| keywords[0].display_name | Artificial intelligence |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.551028311252594 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/deep-learning |
| keywords[2].score | 0.5015552043914795 |
| keywords[2].display_name | Deep learning |
| keywords[3].id | https://openalex.org/keywords/computer-vision |
| keywords[3].score | 0.3521338999271393 |
| keywords[3].display_name | Computer vision |
| keywords[4].id | https://openalex.org/keywords/pattern-recognition |
| keywords[4].score | 0.34986740350723267 |
| keywords[4].display_name | Pattern recognition (psychology) |
| language | en |
| locations[0].id | doi:10.55248/gengpi.5.0524.1358 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4220651630 |
| locations[0].source.issn | 2582-7421 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | 2582-7421 |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | International Journal of Research Publication and Reviews |
| locations[0].source.host_organization | |
| locations[0].source.host_organization_name | |
| locations[0].license | |
| locations[0].pdf_url | https://doi.org/10.55248/gengpi.5.0524.1358 |
| 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 | International Journal of Research Publication and Reviews |
| locations[0].landing_page_url | http://doi.org/10.55248/gengpi.5.0524.1358 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5099059621 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Jalappagari Sainath |
| authorships[0].countries | IN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210134346 |
| authorships[0].affiliations[0].raw_affiliation_string | School of Engineering, Department of AI & ML,Malla Reddy University, Hyderabad -500043, India. |
| authorships[0].institutions[0].id | https://openalex.org/I4210134346 |
| authorships[0].institutions[0].ror | https://ror.org/044s9c536 |
| authorships[0].institutions[0].type | nonprofit |
| authorships[0].institutions[0].lineage | https://openalex.org/I4210134346 |
| authorships[0].institutions[0].country_code | IN |
| authorships[0].institutions[0].display_name | G. M. Reddy Research Foundation |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | J. Sainath |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | School of Engineering, Department of AI & ML,Malla Reddy University, Hyderabad -500043, India. |
| authorships[1].author.id | https://openalex.org/A5111224004 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | M. S. Shankar Reddy |
| authorships[1].countries | IN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I4210134346 |
| authorships[1].affiliations[0].raw_affiliation_string | School of Engineering, Department of AI & ML,Malla Reddy University, Hyderabad -500043, India. |
| authorships[1].institutions[0].id | https://openalex.org/I4210134346 |
| authorships[1].institutions[0].ror | https://ror.org/044s9c536 |
| authorships[1].institutions[0].type | nonprofit |
| authorships[1].institutions[0].lineage | https://openalex.org/I4210134346 |
| authorships[1].institutions[0].country_code | IN |
| authorships[1].institutions[0].display_name | G. M. Reddy Research Foundation |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | M. Saketh Reddy |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | School of Engineering, Department of AI & ML,Malla Reddy University, Hyderabad -500043, India. |
| authorships[2].author.id | https://openalex.org/A5108942294 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Siva Saketh |
| authorships[2].countries | IN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210134346 |
| authorships[2].affiliations[0].raw_affiliation_string | School of Engineering, Department of AI & ML,Malla Reddy University, Hyderabad -500043, India. |
| authorships[2].institutions[0].id | https://openalex.org/I4210134346 |
| authorships[2].institutions[0].ror | https://ror.org/044s9c536 |
| authorships[2].institutions[0].type | nonprofit |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210134346 |
| authorships[2].institutions[0].country_code | IN |
| authorships[2].institutions[0].display_name | G. M. Reddy Research Foundation |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | S. Saketh |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | School of Engineering, Department of AI & ML,Malla Reddy University, Hyderabad -500043, India. |
| authorships[3].author.id | https://openalex.org/A5099059622 |
| authorships[3].author.orcid | |
| authorships[3].author.display_name | Ch. Sakshitha |
| authorships[3].countries | IN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I4210134346 |
| authorships[3].affiliations[0].raw_affiliation_string | School of Engineering, Department of AI & ML,Malla Reddy University, Hyderabad -500043, India. |
| authorships[3].institutions[0].id | https://openalex.org/I4210134346 |
| authorships[3].institutions[0].ror | https://ror.org/044s9c536 |
| authorships[3].institutions[0].type | nonprofit |
| authorships[3].institutions[0].lineage | https://openalex.org/I4210134346 |
| authorships[3].institutions[0].country_code | IN |
| authorships[3].institutions[0].display_name | G. M. Reddy Research Foundation |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Ch. Sakshitha |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | School of Engineering, Department of AI & ML,Malla Reddy University, Hyderabad -500043, India. |
| authorships[4].author.id | https://openalex.org/A5043896025 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | K. Akshay |
| authorships[4].countries | IN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210134346 |
| authorships[4].affiliations[0].raw_affiliation_string | School of Engineering, Department of AI & ML,Malla Reddy University, Hyderabad -500043, India. |
| authorships[4].institutions[0].id | https://openalex.org/I4210134346 |
| authorships[4].institutions[0].ror | https://ror.org/044s9c536 |
| authorships[4].institutions[0].type | nonprofit |
| authorships[4].institutions[0].lineage | https://openalex.org/I4210134346 |
| authorships[4].institutions[0].country_code | IN |
| authorships[4].institutions[0].display_name | G. M. Reddy Research Foundation |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | K. Akshay |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | School of Engineering, Department of AI & ML,Malla Reddy University, Hyderabad -500043, India. |
| authorships[5].author.id | https://openalex.org/A5014672085 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-8109-3610 |
| authorships[5].author.display_name | Thayyaba Khatoon Mohammed |
| authorships[5].countries | IN |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I4210134346 |
| authorships[5].affiliations[0].raw_affiliation_string | School of Engineering, Department of AI & ML,Malla Reddy University, Hyderabad -500043, India. |
| authorships[5].institutions[0].id | https://openalex.org/I4210134346 |
| authorships[5].institutions[0].ror | https://ror.org/044s9c536 |
| authorships[5].institutions[0].type | nonprofit |
| authorships[5].institutions[0].lineage | https://openalex.org/I4210134346 |
| authorships[5].institutions[0].country_code | IN |
| authorships[5].institutions[0].display_name | G. M. Reddy Research Foundation |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Thayyaba Khatoon Mohammed |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | School of Engineering, Department of AI & ML,Malla Reddy University, Hyderabad -500043, India. |
| authorships[6].author.id | https://openalex.org/A5038337279 |
| authorships[6].author.orcid | |
| authorships[6].author.display_name | Prof.A. kalyani |
| authorships[6].author_position | last |
| authorships[6].raw_author_name | Prof.A. kalyani |
| authorships[6].is_corresponding | False |
| has_content.pdf | True |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.55248/gengpi.5.0524.1358 |
| open_access.oa_status | bronze |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Color Detection using Deep Learning Techniques |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10824 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9833999872207642 |
| 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 | Image Retrieval and Classification Techniques |
| related_works | https://openalex.org/W2731899572, https://openalex.org/W3215138031, https://openalex.org/W2058170566, https://openalex.org/W2755342338, https://openalex.org/W2772917594, https://openalex.org/W2775347418, https://openalex.org/W2166024367, https://openalex.org/W3009238340, https://openalex.org/W3116076068, https://openalex.org/W2229312674 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.55248/gengpi.5.0524.1358 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4220651630 |
| best_oa_location.source.issn | 2582-7421 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | 2582-7421 |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | International Journal of Research Publication and Reviews |
| best_oa_location.source.host_organization | |
| best_oa_location.source.host_organization_name | |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://doi.org/10.55248/gengpi.5.0524.1358 |
| 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 | International Journal of Research Publication and Reviews |
| best_oa_location.landing_page_url | http://doi.org/10.55248/gengpi.5.0524.1358 |
| primary_location.id | doi:10.55248/gengpi.5.0524.1358 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4220651630 |
| primary_location.source.issn | 2582-7421 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | 2582-7421 |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | International Journal of Research Publication and Reviews |
| primary_location.source.host_organization | |
| primary_location.source.host_organization_name | |
| primary_location.license | |
| primary_location.pdf_url | https://doi.org/10.55248/gengpi.5.0524.1358 |
| 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 | International Journal of Research Publication and Reviews |
| primary_location.landing_page_url | http://doi.org/10.55248/gengpi.5.0524.1358 |
| publication_date | 2024-05-17 |
| publication_year | 2024 |
| referenced_works | https://openalex.org/W2083486015, https://openalex.org/W1567423711, https://openalex.org/W3032298940, https://openalex.org/W1533162639, https://openalex.org/W2277098554, https://openalex.org/W1983587030, https://openalex.org/W3193779890 |
| referenced_works_count | 7 |
| abstract_inverted_index.a | 3 |
| abstract_inverted_index.an | 84 |
| abstract_inverted_index.be | 83 |
| abstract_inverted_index.in | 10, 61, 94 |
| abstract_inverted_index.of | 6, 25, 37, 92 |
| abstract_inverted_index.to | 71, 82 |
| abstract_inverted_index.and | 15, 31, 43, 48, 75, 96 |
| abstract_inverted_index.are | 52 |
| abstract_inverted_index.for | 18, 40, 59 |
| abstract_inverted_index.the | 23, 35, 57, 90, 98 |
| abstract_inverted_index.This | 0 |
| abstract_inverted_index.also | 53 |
| abstract_inverted_index.data | 74 |
| abstract_inverted_index.deep | 8, 26 |
| abstract_inverted_index.role | 36 |
| abstract_inverted_index.with | 12, 29 |
| abstract_inverted_index.color | 20, 41, 63, 78 |
| abstract_inverted_index.image | 73 |
| abstract_inverted_index.power | 91 |
| abstract_inverted_index.we'll | 88 |
| abstract_inverted_index.where | 87 |
| abstract_inverted_index.OpenCV | 30 |
| abstract_inverted_index.Pillow | 32 |
| abstract_inverted_index.future | 49 |
| abstract_inverted_index.robust | 19 |
| abstract_inverted_index.tandem | 11 |
| abstract_inverted_index.world. | 100 |
| abstract_inverted_index.OpenCV, | 13 |
| abstract_inverted_index.Pillow, | 14 |
| abstract_inverted_index.analyse | 72 |
| abstract_inverted_index.briefly | 54 |
| abstract_inverted_index.concise | 4 |
| abstract_inverted_index.extract | 76 |
| abstract_inverted_index.project | 80 |
| abstract_inverted_index.witness | 89 |
| abstract_inverted_index.abstract | 1 |
| abstract_inverted_index.details, | 45 |
| abstract_inverted_index.dominant | 77 |
| abstract_inverted_index.involves | 67 |
| abstract_inverted_index.journey, | 86 |
| abstract_inverted_index.learning | 9, 27 |
| abstract_inverted_index.metrics, | 47 |
| abstract_inverted_index.overview | 5 |
| abstract_inverted_index.promises | 81 |
| abstract_inverted_index.provides | 2 |
| abstract_inverted_index.research | 50 |
| abstract_inverted_index.colourful | 99 |
| abstract_inverted_index.detection | 64 |
| abstract_inverted_index.discusses | 22 |
| abstract_inverted_index.employing | 68 |
| abstract_inverted_index.potential | 58 |
| abstract_inverted_index.utilizing | 7 |
| abstract_inverted_index.addressed, | 55 |
| abstract_inverted_index.algorithms | 39, 70 |
| abstract_inverted_index.clustering | 16, 38, 69 |
| abstract_inverted_index.directions | 51 |
| abstract_inverted_index.evaluation | 46 |
| abstract_inverted_index.frameworks | 28 |
| abstract_inverted_index.libraries, | 33 |
| abstract_inverted_index.real-world | 62 |
| abstract_inverted_index.techniques | 17 |
| abstract_inverted_index.technology | 93 |
| abstract_inverted_index.emphasizing | 34 |
| abstract_inverted_index.integration | 24 |
| abstract_inverted_index.methodology | 66 |
| abstract_inverted_index.advancements | 60 |
| abstract_inverted_index.detection.It | 21 |
| abstract_inverted_index.highlighting | 56 |
| abstract_inverted_index.illuminating | 85 |
| abstract_inverted_index.interpreting | 97 |
| abstract_inverted_index.quantization | 42 |
| abstract_inverted_index.understanding | 95 |
| abstract_inverted_index.applications.The | 65 |
| abstract_inverted_index.information.This | 79 |
| abstract_inverted_index.segmentation.Implementation | 44 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.6700000166893005 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile.value | 0.55909702 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |