Mango_deep_yield_dataset koirala et al. 2021
收藏DataCite Commons2021-02-15 更新2025-04-09 收录
下载链接:
https://acquire.cqu.edu.au/articles/dataset/Mango_deep_yield_dataset_koirala_et_al_2021/14033993/1
下载链接
链接失效反馈官方服务:
资源简介:
Koirala, A.; Walsh, K.B.; Wang, Z. Attempting to Estimate the Unseen – Correction for Occluded Fruit in Tree Fruit Load Estimation by Machine Vision with Deep Learning.<br>This dataset contains dual-view images (image from two opposite sides (sideA and sideB) of a tree) used in the paper "Attempting to estimate the unseen - correction for occluded fruit in tree fruit load estimation by machine vision with deep learning".There are three orchards A, B and C with images of same trees from two seasons (2017 and 2018). For each season ABC is the collection of images from orchards A, B and C put together.A-x, B-x and C-x comprise of extended set of images collected in season 2017.<br>A= 17 treesB= 6 treesC= 12 treesABC= 35 trees<br>A-x= 44 treesB-x= 19 treesC-x= 35 treesABC-x = 98 trees<br>harvest_data_deep_yield.xlsx file contains the harvest fruit count mapped with the tree and image names for each orchard.
提供机构:
CQUniversity
创建时间:
2021-02-15



