@inproceedings{Liu2018243,
	series = {Proceedings - 2017 {IEEE} 5th {International} {Symposium} on {Robotics} and {Intelligent} {Sensors}, {IRIS} 2017},
	title = {Visual inspection system for smart manufacture of home appliances},
	volume = {2018-January},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047415773&doi=10.1109%2fIRIS.2017.8250129&partnerID=40&md5=1af48014953054346b18d0cdadb128e6},
	doi = {10.1109/IRIS.2017.8250129},
	abstract = {Home appliance manufacturing involves a lot of human operations due to variety of products and sizes, and lower cost requirements. Applying traditional inspection solutions to home appliances faces three challenging issues: 1)hard to handle different sizes of objects from big refrigerators to small kettles with fixed camera setting; 2)heavy engineering and tuning work for different inspection tasks; 3)high cost of stand-alone inspection system. This paper proposes a camera mounted robot solution with self-learning and edge/cloud visual inspection architecture. Firstly the 4 DoF robot arm with novel controlling strategy uses a single camera to handle variety of objects. For different inspection tasks, a machine learning based approach removes the complicated and tedious works for engineering and parameter tuning. Lastly, an edge/cloud computing framework puts limited tasks on cheap edge devices at manufacturing side and reduces the total cost. © 2017 IEEE.},
	author = {Liu, T. and Gu, H. and Wang, D.},
	year = {2018},
	note = {tex.document\_type: Conference Paper
tex.source: Scopus},
	keywords = {\#nosource},
	pages = {243--248},
}

{"_id":"oifxNxxA5ypecrMp3","bibbaseid":"liu-gu-wang-visualinspectionsystemforsmartmanufactureofhomeappliances-2018","author_short":["Liu, T.","Gu, H.","Wang, D."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","series":"Proceedings - 2017 IEEE 5th International Symposium on Robotics and Intelligent Sensors, IRIS 2017","title":"Visual inspection system for smart manufacture of home appliances","volume":"2018-January","url":"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047415773&doi=10.1109%2fIRIS.2017.8250129&partnerID=40&md5=1af48014953054346b18d0cdadb128e6","doi":"10.1109/IRIS.2017.8250129","abstract":"Home appliance manufacturing involves a lot of human operations due to variety of products and sizes, and lower cost requirements. Applying traditional inspection solutions to home appliances faces three challenging issues: 1)hard to handle different sizes of objects from big refrigerators to small kettles with fixed camera setting; 2)heavy engineering and tuning work for different inspection tasks; 3)high cost of stand-alone inspection system. This paper proposes a camera mounted robot solution with self-learning and edge/cloud visual inspection architecture. Firstly the 4 DoF robot arm with novel controlling strategy uses a single camera to handle variety of objects. For different inspection tasks, a machine learning based approach removes the complicated and tedious works for engineering and parameter tuning. Lastly, an edge/cloud computing framework puts limited tasks on cheap edge devices at manufacturing side and reduces the total cost. © 2017 IEEE.","author":[{"propositions":[],"lastnames":["Liu"],"firstnames":["T."],"suffixes":[]},{"propositions":[],"lastnames":["Gu"],"firstnames":["H."],"suffixes":[]},{"propositions":[],"lastnames":["Wang"],"firstnames":["D."],"suffixes":[]}],"year":"2018","note":"tex.document_type: Conference Paper tex.source: Scopus","keywords":"#nosource","pages":"243–248","bibtex":"@inproceedings{Liu2018243,\n\tseries = {Proceedings - 2017 {IEEE} 5th {International} {Symposium} on {Robotics} and {Intelligent} {Sensors}, {IRIS} 2017},\n\ttitle = {Visual inspection system for smart manufacture of home appliances},\n\tvolume = {2018-January},\n\turl = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047415773&doi=10.1109%2fIRIS.2017.8250129&partnerID=40&md5=1af48014953054346b18d0cdadb128e6},\n\tdoi = {10.1109/IRIS.2017.8250129},\n\tabstract = {Home appliance manufacturing involves a lot of human operations due to variety of products and sizes, and lower cost requirements. Applying traditional inspection solutions to home appliances faces three challenging issues: 1)hard to handle different sizes of objects from big refrigerators to small kettles with fixed camera setting; 2)heavy engineering and tuning work for different inspection tasks; 3)high cost of stand-alone inspection system. This paper proposes a camera mounted robot solution with self-learning and edge/cloud visual inspection architecture. Firstly the 4 DoF robot arm with novel controlling strategy uses a single camera to handle variety of objects. For different inspection tasks, a machine learning based approach removes the complicated and tedious works for engineering and parameter tuning. Lastly, an edge/cloud computing framework puts limited tasks on cheap edge devices at manufacturing side and reduces the total cost. © 2017 IEEE.},\n\tauthor = {Liu, T. and Gu, H. and Wang, D.},\n\tyear = {2018},\n\tnote = {tex.document\\_type: Conference Paper\ntex.source: Scopus},\n\tkeywords = {\\#nosource},\n\tpages = {243--248},\n}\n\n\n\n","author_short":["Liu, T.","Gu, H.","Wang, D."],"key":"Liu2018243","id":"Liu2018243","bibbaseid":"liu-gu-wang-visualinspectionsystemforsmartmanufactureofhomeappliances-2018","role":"author","urls":{"Paper":"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047415773&doi=10.1109%2fIRIS.2017.8250129&partnerID=40&md5=1af48014953054346b18d0cdadb128e6"},"keyword":["#nosource"],"metadata":{"authorlinks":{}},"downloads":0,"html":""},"bibtype":"inproceedings","biburl":"https://bibbase.org/zotero/maraee75","dataSources":["PjpadRRabZA7FRKpn"],"keywords":["#nosource"],"search_terms":["visual","inspection","system","smart","manufacture","home","appliances","liu","gu","wang"],"title":"Visual inspection system for smart manufacture of home appliances","year":2018}