62. Automatic estimation of trunk cross sectional area using deep learning-Reference-Cited by-同舟云学术

62. Automatic estimation of trunk cross sectional area using deep learning

Published:2023-07-02 Issue: Volume: Page:
ISSN:
Container-title:Precision agriculture ’23
language:
Short-container-title:

Author:

Wang T.¹,Sankari P.¹,Brown J.¹,Paudel A.²,He L.¹,Karkee M.²,Thompson A.³,Grimm C.¹,Davidson J.R.¹,Todorovic S.¹

Affiliation:

1. Collaborative Robotics & Intelligent Systems Institute, Oregon State University, Corvallis, OR 97331, USA.

2. Center for Precision & Automated Agricultural Systems, Washington State University, Prosser WA 99350, USA.

3. Department of Horticulture, Oregon State University, Corvallis, OR 97331, USA.

Publisher

Wageningen Academic Publishers

Link

https://www.wageningenacademic.com/doi/pdf/10.3920/978-90-8686-947-3_62

Reference10 articles.

1. Bargoti, S., Underwood, J.P., Nieto, J.I., and Sukkarieh, S. (2013). A pipeline for trunk localisation using lidar in trellis structured orchards. In: Mejias, L., Corke, P. and Roberts, J. (eds.): Results of the 9th Int’l Conf. on Field & Service Robotics., New York City, USA: Springer Publishing, pp. 455-468.

2. Breast Height Diameter Estimation From High-Density Airborne LiDAR Data

3. Masked-attention Mask Transformer for Universal Image Segmentation

4. Kan, J., Li, W., and Sun, R. (2008). Automatic measurement of trunk and branch diameter of standing trees based on computer vision. In: Proc. of the 3rd IEEE Conf. on Industrial Electronics & Applications. IEEE, New York City, U.S.A., pp. 995-998.

5. Correlation of trunk cross sectional area with fruit yield, quality and leaf nutrient status in plum under North West Himalayan region of India

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1. Evaluation of Computer Vision Systems and Applications to Estimate Trunk Cross-Sectional Area, Flower Cluster Number, Thinning Efficacy and Yield of Apple;Horticulturae;2023-08-03