Deep count: Fruit counting based on deep simulated learning

Sensors (Switzerland)

Volumn 17, Issue 4, 2017, Pages

  Rahnemoonfar, Maryam ^a   Sheppard, Clay ^a  

^a TEXAS A AND M UNIVERSITY CORPUS CHRISTI   (United States)

Author keywords

Agricultural sensors; Deep learning; Simulated learning; Yield estimation

Indexed keywords

AGRICULTURE; CULTIVATION; DEEP LEARNING; FRUITS; NEURAL NETWORKS; SAMPLING;

CONVOLUTIONAL NEURAL NETWORK; CURRENT PRACTICES; SIMULATED LEARNING; SYNTHETIC DATA; SYNTHETIC IMAGES; TRAINING SAMPLE; VIABLE SOLUTIONS; YIELD ESTIMATION;

DEEP NEURAL NETWORKS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; MACHINE LEARNING;

ALGORITHMS; MACHINE LEARNING; NEURAL NETWORKS (COMPUTER);

EID: 85018513324     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s17040905     Document Type: Article

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