@article {aFerrer-Ferrer, title = {Simultaneous Fruit Detection and Size Estimation Using Multitask Deep Neural Networks }, journal = {Biosystems Engineering}, volume = {233}, year = {2023}, month = {09/2023}, pages = {63-75}, abstract = {

The measurement of fruit size is of great interest to estimate the yield and predict the harvest resources in advance. This work proposes a novel technique for in-field apple detection and measurement based on Deep Neural Networks. The proposed\ \ framework was trained with RGB-D data and consists of an end-to-end multitask Deep Neural Network architecture 13 specifically designed to perform the following tasks: 1) detection and segmentation of each fruit from its surroundings; 2) estimation of the diameter of each detected fruit. The methodology was tested with a total of 15335 annotated apples at different growth stages, with diameters varying from 27 mm to 95 mm. Fruit detection results reported an F1-score for apple detection of 0.88 and a mean absolute error of diameter estimation of 5.64 mm. These are state-of-the-art results with the additional advantages of: a) using an end-to-end multitask trainable network; b) an efficient and fast inference speed; and c) being based on RGB-D data which can be acquired with affordable depth cameras. On the contrary, the main disadvantage is the need of annotating a large amount of data with fruit masks and diameter ground truth to train the model. Finally, a fruit visibility analysis showed an improvement in the prediction when limiting the measurement to apples above 65\% of visibility (mean absolute error of 5.09 mm). This suggests that future works should develop a method for automatically identifying the most visible apples and discard the prediction of highly occluded fruits.

}, keywords = {deep learning, Fruit measurement, Fruit visibility, Precision agriculture, Yield estimation}, doi = {https://doi.org/10.1016/j.biosystemseng.2023.07.010}, author = {Ferrer-Ferrer, M. and Ruiz-Hidalgo, J. and Gregorio, Eduard and Ver{\'o}nica Vilaplana and Morros, J.R. and Gen{\'e}-Mola, Jordi} }