001439019 000__ 03410cam\a2200601\i\4500
001439019 001__ 1439019
001439019 003__ OCoLC
001439019 005__ 20230309004406.0
001439019 006__ m\\\\\o\\d\\\\\\\\
001439019 007__ cr\un\nnnunnun
001439019 008__ 210821s2021\\\\si\a\\\\ob\\\\000\0\eng\d
001439019 020__ $$a9789811635014$$q(electronic bk.)
001439019 020__ $$a9811635013$$q(electronic bk.)
001439019 020__ $$z9789811635007
001439019 020__ $$z9811635005
001439019 0247_ $$a10.1007/978-981-16-3501-4$$2doi
001439019 035__ $$aSP(OCoLC)1264457737
001439019 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dGW5XE$$dOCLCO$$dOCLCF$$dN$T$$dEBLCP$$dUKAHL$$dOCLCO$$dOCLCQ
001439019 049__ $$aISEA
001439019 050_4 $$aQK495.G74$$bP36 2021
001439019 08204 $$a584/.9$$223
001439019 1001_ $$aPan, Xin,$$eauthor.
001439019 24510 $$aComputer vision based identification and mosaic of gramineous grass seeds /$$cXin Pan, Xuanhe Zhao, Weihong Yan, Jiangping Liu, Xiaoling Luo, Tana Wuyun.
001439019 264_1 $$aSingapore :$$bSpringer ;$$aBeijing :$$bChina Agricultural Science and Technology Press,$$c[2021]
001439019 264_4 $$c©2021
001439019 300__ $$a1 online resource :$$billustrations (chiefly color)
001439019 336__ $$atext$$btxt$$2rdacontent
001439019 337__ $$acomputer$$bc$$2rdamedia
001439019 338__ $$aonline resource$$bcr$$2rdacarrier
001439019 504__ $$aIncludes bibliographical references.
001439019 5050_ $$aIntroduction -- Forage Identification and Experimental Materials -- Identification of Gramineous Grass Seeds Using Gabor and Locality Preserving Projections -- Identification of Gramineous Grass Seeds Using Difference of Local Fractal Dimensions -- Identification of Gramineous Grass Seeds Using Local Similarity Pattern and Linear Discriminant Analysis -- Identification of Gramineous Grass Seeds Using Local Similarity Pattern and Gray Level Co-occurrence Matrix -- Microscopic Image Mosaic of Gramineous Grass Seeds -- Digital Information Platform of Grassland and Forage Based on Computer Vision.
001439019 506__ $$aAccess limited to authorized users.
001439019 520__ $$aThis book mainly deals with grassland digitalization and recognition through computer vision, which will make contributions to implement of grass auto recognition and data acquisition. Taking advantage of computer vision, it focuses on intrinsic feature extraction to realize the functions such as auto recognition of forage seeds and microscope images mosaic. The book presents a new approach for identification of grass seeds, with clear figures and detailed tables. It enlightens reader by solving the traditional problems of pratacultural science through the aid of computer science.
001439019 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed August 27, 2021).
001439019 650_0 $$aGrasses$$xIdentification.
001439019 650_0 $$aComputer vision.
001439019 650_0 $$aPattern recognition systems.
001439019 650_6 $$aVision par ordinateur.
001439019 650_6 $$aReconnaissance des formes (Informatique)
001439019 655_7 $$aField guides.$$2fast$$0(OCoLC)fst01940354
001439019 655_0 $$aElectronic books.
001439019 7001_ $$aZhao, Xuanhe,$$eauthor.
001439019 7001_ $$aYan, Weihong,$$eauthor.
001439019 7001_ $$aLiu, Jiangping,$$eauthor.
001439019 7001_ $$aLuo, Xiaoling,$$eauthor.
001439019 7001_ $$aWuyun, Tana,$$eauthor.
001439019 77608 $$iPrint version:$$z9811635005$$z9789811635007$$w(OCoLC)1250511455
001439019 852__ $$bebk
001439019 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-3501-4$$zOnline Access$$91397441.1
001439019 909CO $$ooai:library.usi.edu:1439019$$pGLOBAL_SET
001439019 980__ $$aBIB
001439019 980__ $$aEBOOK
001439019 982__ $$aEbook
001439019 983__ $$aOnline
001439019 994__ $$a92$$bISE