{"_buckets": {"deposit": "c2a1fc11-872e-4d5b-ad41-02f7e119925c"}, "_deposit": {"created_by": 45, "id": "6189", "owner": "45", "owners": [45], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "recid", "value": "6189"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/6189", "sets": ["user-uit"]}, "communities": ["uit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "University Classroom Attendance System Using Face Recognition Technique", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "There are rules and principles to obey for everywhere. And also there are various rules to obey for every staff, students and teachers in every University. Among many rules, each student must be full the defined the attendance record percentage. The attendance record is an important role for the evaluation of each student for classroom participation. For instance, if the attendance of the lecture must be full 75 percentage for each subject, it defines that the student can perform in exam well and can know well for that subject. So, only the students having at least 75 percentage attendance can sit the exam. There are many ways to take the attendance record. Nowadays, the attendance management system is by using QR code, fingerprint recognition, face recognition, etc. And also, in many applications, face recognition become popular to use and it is used for tracing the criminals, for payment, for access right and for taking the attendance because it is reliable, convenience, inexpensive, and easy to use. This proposed system is the classroom automatic attendance system for the University by using face recognition technique Deep Learning technique is used for this system. CNN (Convolutional neural network) is one of deep neural networks. There are many famous CNN models (LeNet, AlexNet, GoogleNet, VGGNet, ResNet, FaceNet, etc). In the proposed system, FaceNet is used for feature extraction and Support vector machine is used for face classification of students. The result of proposed system is compared to the results of RestNet model. The proposed system can be used to reduce time consuming and paper works and can also replace the manual system with the automated attendance system."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "deep learning"}, {"interim": "face recognition"}, {"interim": "FaceNet"}, {"interim": "convolutional neural network"}, {"interim": "support vector machine"}, {"interim": "ResNet"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-11-17"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "University Classroom Attendance System Using Face Recognition Technique.pdf", "filesize": [{"value": "373 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "mimetype": "application/pdf", "size": 373000.0, "url": {"url": "https://meral.edu.mm/record/6189/files/University Classroom Attendance System Using Face Recognition Technique.pdf"}, "version_id": "527a4052-eb20-49de-a290-348a294f68ca"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_journal_title": "UJRI"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Thida Nyein"}, {"subitem_authors_fullname": "Aung Nway Oo"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Journal article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2019-10-01"}, "item_title": "University Classroom Attendance System Using Face Recognition Technique", "item_type_id": "21", "owner": "45", "path": ["1596102355557"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000006189", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-11-17"}, "publish_date": "2020-11-17", "publish_status": "0", "recid": "6189", "relation": {}, "relation_version_is_last": true, "title": ["University Classroom Attendance System Using Face Recognition Technique"], "weko_shared_id": -1}