A predictive model for turfgrass color and quality evaluation using deep learning and UAV imageries

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 10218, Issue , 2017, Pages

  Phan, Claude ^a   Raheja, Amar ^a   Bhandari, Subodh ^a   Green, Robert L ^b   Do, Dat ^a  

^a Dept of Computer Science ^*  (United States)

^b CALIFORNIA STATE POLYTECHNIC UNIVERSITY   (United States)

Author keywords

Deep Learning; Machine Learning; UAV

Indexed keywords

AGRICULTURAL MACHINERY; AGRICULTURE; ARTIFICIAL INTELLIGENCE; CARBON; COLOR; CONSERVATION; EDUCATION; IMAGE QUALITY; IRRIGATION; LEARNING ALGORITHMS; LEARNING SYSTEMS; PERSONAL COMPUTERS; QUALITY CONTROL; SCHEDULING; UNMANNED AERIAL VEHICLES (UAV); WATER; WATER CONSERVATION; WATER SUPPLY;

COMPUTATIONAL APPROACH; ENVIRONMENTAL QUALITY; IRRIGATION WATER USE EFFICIENCY; LEARNING TECHNIQUES; MACHINE LEARNING APPROACHES; PREDICTIVE MODELING; SOIL CARBON SEQUESTRATION; TURFGRASS MANAGEMENT;

DEEP LEARNING;

EID: 85021841195     PISSN: 0277786X     EISSN: 1996756X     Source Type: Conference Proceeding    
DOI: 10.1117/12.2262042     Document Type: Conference Paper

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