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https://rda.sliit.lk/handle/123456789/3148
Title: | Intelligent System for Skin Disease Detection of Dogs with Ontology Based Clinical Information Extraction |
Authors: | Rathnayaka, R. M. N. A Anuththara, K. G. S. N Wickramasinghe, R.J.P Gimhana, P. S Weerasinghe, L Wimalaratne, G |
Keywords: | Artificial Intelligence CNN Deep Learning Image Processing Information Extraction Knowledge Base Natural Language Processing Ontology Sentiment Analysis Supervised Learning |
Issue Date: | 29-Oct-2022 |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Citation: | R. 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. |
Series/Report no.: | 2022 IEEE 13th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2022;Pages 59 - 66 |
Abstract: | The 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%. |
URI: | https://rda.sliit.lk/handle/123456789/3148 |
ISBN: | 978-166549299-7 |
Appears in Collections: | Department of Information Technology |
Files in This Item:
File | Description | Size | Format | |
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Intelligent_System_for_Skin_Disease_Detection_of_Dogs_with_Ontology_Based_Clinical_Information_Extraction.pdf Until 2050-12-31 | 2.14 MB | Adobe PDF | View/Open Request a copy |
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