A novel apple fruit detection and counting methodology based on deep learning and trunk tracking in modern orchard-Reference-Cited by-同舟云学术

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A novel apple fruit detection and counting methodology based on deep learning and trunk tracking in modern orchard

Published:2022-06 Issue: Volume:197 Page:107000
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Gao Fangfang,Fang Wentai,Sun Xiaoming,Wu Zhenchao,Zhao Guanao,Li Guo,Li Rui,Fu Longsheng,Zhang Qin

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference54 articles.

1. Deep learning techniques for estimation of the yield and size of citrus fruits using a UAV;Apolo-Apolo;Eur. J. Agron.,2020

2. Image segmentation for fruit detection and yield estimation in apple orchards;Bargoti;J. Field Rob.,2017

3. Counting apples and oranges with deep learning: A data-driven approach;Chen;IEEE Rob. Autom. Lett.,2017

4. Accurate scale estimation for robust visual tracking;Danelljan,2014

5. Semantic mapping for orchard environments by merging two-sides reconstructions of tree rows;Dong;J. Field Rob.,2020

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