Comparing U-Net convolutional network with mask R-CNN in the performances of pomegranate tree canopy segmentation

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 10780, Issue , 2018, Pages

  Zhao, Tiebiao ^a   Yang, Yonghuan ^b   Niu, Haoyu ^a   Wang, Dong ^c   Chen, Yangquan ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b SANTA CLARA UNIVERSITY   (United States)

^c U S DEPARTMENT OF AGRICULTURE   (United States)

Author keywords

Canopy Segmentation; Instance aware Segmentation; Mask R CNN; Pomegranate Trees; U net CNN

Indexed keywords

AIRCRAFT DETECTION; ANTENNAS; CONVOLUTION; CROPS; DEEP LEARNING; FORESTRY; IMAGE ENHANCEMENT; PIXELS; PLANTS (BOTANY); PRECISION AGRICULTURE; REMOTE SENSING; TREES (MATHEMATICS); UNMANNED AERIAL VEHICLES (UAV);

CONVOLUTIONAL NETWORKS; HIGH RESOLUTION VISIBLE; LEARNING TECHNOLOGY; LOW RESOLUTION IMAGES; MULTISPECTRAL IMAGES; PIXEL CLASSIFICATION; POMEGRANATE TREES; VERY HIGH RESOLUTION;

IMAGE SEGMENTATION;

EID: 85058223848     PISSN: 0277786X     EISSN: 1996756X     Source Type: Conference Proceeding    
DOI: 10.1117/12.2325570     Document Type: Conference Paper

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