{"created":"2021-01-21T08:38:33.475437+00:00","id":7709,"links":{},"metadata":{"_buckets":{"deposit":"de0ad58c-cbfb-4db2-877b-c673cd57eb52"},"_deposit":{"created_by":92,"id":"7709","owner":"92","owners":[92],"owners_ext":{"displayname":"","email":"khin_sandar_chit@miit.edu.mm","username":""},"pid":{"revision_id":0,"type":"depid","value":"7709"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/00007709","sets":["1582963674932","1582963674932:1597397014014"]},"communities":["miit"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Leaves Disease and Damage Rate Classification based on Features","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"\"This paper uses\nthe image processing techniques to detect transform of color on\nthe leaf and classify the disease based on the color values. This\npaper uses region base segmentation based on RGB color value.\nPaddy leaf is segmented on color feature value and classify these\ncolor values to support decisions for disease type. Image\nenhancement process start to eliminate noise in an image and\nnext is object extraction. The system uses median filter\ntechnique and segment the object in color regions. Analysis of\ncolor region value and the texture of leaf classified the damage\nrate and diseases.\""}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"Segmentation"},{"interim":"HSV Colour"},{"interim":"Texture"},{"interim":"Image"},{"interim":"Feature"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2021-01-21"}],"displaytype":"preview","filename":"Leaves Disease and Damage Rate Classification based on Features (IEEE-GCCE2019).pdf","filesize":[{"value":"305 KB"}],"format":"application/pdf","licensetype":"license_0","url":{"url":"https://meral.edu.mm/record/7709/files/Leaves Disease and Damage Rate Classification based on Features (IEEE-GCCE2019).pdf"},"version_id":"1decb39e-2483-4330-a27c-b3ccb5404238"}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"IEEE GCCE","subitem_c_date":"2019-Oct","subitem_conference_title":"2019 IEEE 8th Global Conference on Consumer Electronic (GCCE 2019)","subitem_part":"62","subitem_place":"Japan","subitem_session":"OS-ICE1: Deep Learning plus Internet of Things & Applications to Consumer Electronics"}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Mie Mie Tin"},{"subitem_authors_fullname":"Mie Mie Khin"},{"subitem_authors_fullname":"Su Su Hlaing"},{"subitem_authors_fullname":"Phyo Phyo Wai"},{"subitem_authors_fullname":"Khin lay Mon"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Conference paper"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2019-10-15"},"item_title":"Leaves Disease and Damage Rate Classification based on Features","item_type_id":"21","owner":"92","path":["1582963674932","1597397014014"],"publish_date":"2021-01-21","publish_status":"0","recid":"7709","relation_version_is_last":true,"title":["Leaves Disease and Damage Rate Classification based on Features"],"weko_creator_id":"92","weko_shared_id":-1},"updated":"2021-12-13T04:10:46.747867+00:00"}