Proceedings

Find matching any: Reset
Bier, J
Van Beers, R
Add filter to result:
Authors
Wouters, N
Van Beers, R
De Ketelaere, B
Deckers, T
De Baerdemaeker, J
Saeys, W
Sridharan, S
Sornapudi, S
Hu, Q
Kumpatla, S
Bier, J
Topics
Sensor Application in Managing In-season CropVariability
Big Data, Data Mining and Deep Learning
Type
Oral
Year
2014
2022
Home » Authors » Results

Authors

Filter results2 paper(s) found.

1. Towards Automated Pneumatic Thinning Of Floral Buds On Pear Trees

Thinning of pome and stone fruit is an important horticultural practice that is used to enhance fruit set and quality by removing excess floral buds. As it is still mostly conducted through manual labor, thinning comprises a large part of a grower’s production costs. Various thinning machines developed in recent years have clearly demonstrated that mechanization of this technique is both feasible and cost effective. Generally, these machines still lack sufficient selectivity... N. Wouters, R. Van beers, B. De ketelaere, T. Deckers, J. De baerdemaeker, W. Saeys

2. A Generative Adversarial Network-based Method for High Fidelity Synthetic Data Augmentation

Digital Agriculture has led to new phenotyping methods that use artificial intelligence and machine learning solutions on image and video data collected from lab, greenhouse, and field environments. The availability of accurately annotated image and video data remains a bottleneck for developing most machine learning and deep learning models. Typically, deep learning models require thousands of unique samples to accurately learn a given task. However, manual annotation of a large dataset will... S. Sridharan, S. Sornapudi, Q. Hu, S. Kumpatla, J. Bier