{"_buckets": {"deposit": "02499ff2-6c8f-4fca-b6c6-eaf1605b420b"}, "_deposit": {"created_by": 45, "id": "5410", "owner": "45", "owners": [45], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "recid", "value": "5410"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/5410", "sets": ["user-uit"]}, "communities": ["uit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Automatic Assessing Body Condition Score from Digital Images by Active Shape Model and Multiple Regression Technique", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Body Condition Score (BCS) of a dairy cow is a magnificent indicator for determining energy reserves of cows. The\npurpose of this study is to assess BCS of dairy cattle by analyzing cows’ rear-view images. In order to do so, we first\nmodel shape of cow’s tailhead area by using active shape model. Then, angle features are modelled as multiple\nregression model for estimating scores. The experimental results show that proposed system is promising compared\nto some existing methods."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Body Condition Score"}, {"interim": "Active Shape Model"}, {"interim": "Multiple Regression Analysis"}, {"interim": "Angle features"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_no", "licensefree": "© The 2017 International Conference on Artificial Life and Robotics (ICAROB 2017)", "licensetype": "license_0"}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "ICAROB", "subitem_c_date": "19-22 January, 2017", "subitem_conference_title": "The 2017 International Conference on Artificial Life and Robotics", "subitem_place": "Seagaia Convention Center, Miyazaki, Japan", "subitem_website": "https://alife-robotics.co.jp/LP/2017/OS20-3.htm"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Nay Chi Lynn"}, {"subitem_authors_fullname": "Thi Thi Zin"}, {"subitem_authors_fullname": "Ikuo Kobayashi"}]}]}, "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": "2017-01-22"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "10.5954/icarob.2017.os20-3"}, "item_title": "Automatic Assessing Body Condition Score from Digital Images by Active Shape Model and Multiple Regression Technique", "item_type_id": "21", "owner": "45", "path": ["1596102391527"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000005410", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-09-16"}, "publish_date": "2020-09-16", "publish_status": "0", "recid": "5410", "relation": {}, "relation_version_is_last": true, "title": ["Automatic Assessing Body Condition Score from Digital Images by Active Shape Model and Multiple Regression Technique"], "weko_shared_id": -1}