{"_buckets": {"deposit": "8edf59cc-84f9-417b-97da-16d2952bc3b8"}, "_deposit": {"id": "3465", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "3465"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/3465", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Tomato Plant Disease Classification for Mobile Phone Image Using SIFTBeta Feature and Color Statistical Feature", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Plant disease classification is essential forfood productivity and disease diagnosis inagricultural domain. The probability distribution andstatistical properties are essential in imageprocessing to define the features of typical image.The general usage of (Scale Invariant FeatureTransform) SIFT has local feature extraction andglobal feature extraction (bag-Of-Featuresapproach) for classification, and its classificationresult for unknown data also depends on code book(global feature) generation. Instead of using bag-Of-Feature approach, we proposed to apply Betaprobability distribution model for SIFT to be directlyrepresent the image information and then formedSIFT-Beta. The color statistics feature is extractedfrom RGB color space and then combines with SIFTBetato produce proposed features. The proposedfeature is applied in Support Vector Machineclassifier. The classifier is trained for seven labels oftomato with six diseases and healthy."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value": []}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-07-23"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "ICCA 2019 Proceedings Book-pages-233-239.pdf", "filesize": [{"value": "506 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 506000.0, "url": {"url": "https://meral.edu.mm/record/3465/files/ICCA 2019 Proceedings Book-pages-233-239.pdf"}, "version_id": "1932e2d2-0c14-4be3-8bc5-246492808a2c"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Seventeenth International Conference on Computer Applications(ICCA 2019)", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Hlaing, Chit Su"}, {"subitem_authors_fullname": "Zaw, Sai Maung Maung"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2019-02-27"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/1212"}, "item_title": "Tomato Plant Disease Classification for Mobile Phone Image Using SIFTBeta Feature and Color Statistical Feature", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000003465", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-23"}, "publish_date": "2019-07-23", "publish_status": "0", "recid": "3465", "relation": {}, "relation_version_is_last": true, "title": ["Tomato Plant Disease Classification for Mobile Phone Image Using SIFTBeta Feature and Color Statistical Feature"], "weko_shared_id": -1}