Mango_deep_yield_dataset koirala et al. 2021

<div>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.</div><div><br></div><div>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".</div><div>There are three orchards A, B and C with images of same trees from two seasons (2017 and 2018). </div><div>For each season ABC is the collection of images from orchards A, B and C put together.</div><div>A-x, B-x and C-x comprise of extended set of images collected in season 2017.</div><div><br></div><div>A= 17 trees</div><div>B= 6 trees</div><div>C= 12 trees</div><div>ABC= 35 trees</div><div><br></div><div>A-x= 44 trees</div><div>B-x= 19 trees</div><div>C-x= 35 trees</div><div>ABC-x = 98 trees</div><div><br></div><div>harvest_data_deep_yield.xlsx file contains the harvest fruit count mapped with the tree and image names for each orchard.</div>