Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3148
Full metadata record
DC FieldValueLanguage
dc.contributor.authorRathnayaka, R. M. N. A-
dc.contributor.authorAnuththara, K. G. S. N-
dc.contributor.authorWickramasinghe, R.J.P-
dc.contributor.authorGimhana, P. S-
dc.contributor.authorWeerasinghe, L-
dc.contributor.authorWimalaratne, G-
dc.date.accessioned2023-01-24T03:30:58Z-
dc.date.available2023-01-24T03:30:58Z-
dc.date.issued2022-10-29-
dc.identifier.citationR. M. N. A. Rathnayaka, K. G. S. N. Anuththara, R. J. P. Wickramasinghe, P. S. Gimhana, L. Weerasinghe and G. Wimalaratne, "Intelligent System for Skin Disease Detection of Dogs with Ontology Based Clinical Information Extraction," 2022 IEEE 13th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York, NY, NY, USA, 2022, pp. 0059-0066, doi: 10.1109/UEMCON54665.2022.9965696.en_US
dc.identifier.isbn978-166549299-7-
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/3148-
dc.description.abstractThe largest organ in dogs, the epidermis, is crucial in supplying immunological responses. Skin will preserve all the nutrients and safeguard the cells while warding off harmful or pathogenic substances. Most dog owners today are not aware that their pet dog has a skin condition. Although they were aware of these ailments, they had no notion of how to cure them. In such a situation, the dog may experience pain and an aggravation of the condition. Owners should therefore take their dogs to the vet, even if the skin condition is minor. It can, however, be a costly procedure. There aren't many forums where dog owners may get advice from professionals and ask inquiries regarding their pets. The solution suggests a fully functional mobile application which is a combination of disease identification feature, disease severity level detection feature, domain specific knowledge base with semantic web development and a domain specific AI based chat-bot to the dog owners to overcome this problem using Convolutional Neural Network (CNN) and natural language processing (NLP).System will extract the necessary features from the images of the lesion to classify the skin condition and Severity level of the disease. The results obtained show disease type classification is within the accuracy range of 77.78% to 100% which tested again 4 CNN base models. As for the severity level identification accuracy situated around 99.62%.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofseries2022 IEEE 13th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2022;Pages 59 - 66-
dc.subjectArtificial Intelligenceen_US
dc.subjectCNNen_US
dc.subjectDeep Learningen_US
dc.subjectImage Processingen_US
dc.subjectInformation Extractionen_US
dc.subjectKnowledge Baseen_US
dc.subjectNatural Language Processingen_US
dc.subjectOntologyen_US
dc.subjectSentiment Analysisen_US
dc.subjectSupervised Learningen_US
dc.titleIntelligent System for Skin Disease Detection of Dogs with Ontology Based Clinical Information Extractionen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/UEMCON54665.2022.9965696en_US
Appears in Collections:Department of Information Technology

Files in This Item:
File Description SizeFormat 
Intelligent_System_for_Skin_Disease_Detection_of_Dogs_with_Ontology_Based_Clinical_Information_Extraction.pdf
  Until 2050-12-31
2.14 MBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.