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Price, R.R
Palacios, F
Phillips, S.B
Perulli, G
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Authors
Phillips, S.B
Bresilla, K
Manfrini, L
Boini, A
Perulli, G
Morandi, B
Grappadelli, L.C
Tardaguila, J
Palacios, F
Diago, M
Moreda , E.A
Price, R.R
Johnson, R.M
Viator, R.P
Topics
Precision A-Z for Practitioners
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Geospatial Data
Type
Poster
Oral
Year
2010
2018
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1. Optical Sensor Advancements In Latin America

Placeholder... S.B. Phillips

2. Using Deep Learning - Convolutional Naural Networks (CNNS) for Real-Time Fruit Detection in the Tree

Image/video processing for fruit detection in the tree using hard-coded feature extraction algorithms have shown high accuracy on fruit detection during recent years. While accurate, these approaches even with high-end hardware are still computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks architecture based on single-stage detectors. Using deep-learning techniques eliminates the need for hard-code specific features for specific... K. Bresilla, L. Manfrini, A. Boini, G. Perulli, B. Morandi, L.C. Grappadelli

3. Innovative Assessment of Cluster Compactness in Wine Grapes from Automated On-the-Go Proximal Sensing Application

Grape cluster compactness affects berry ripening homogeneity, fungal disease incidence, grape composition and wine quality. Therefore, assessing cluster compactness is crucial for sorting wine grapes for the wine industry. Nowadays, cluster compactness assessing methodology is based either on visual inspection performed by trained evaluators (OIV method) or on morphological features of clusters. The goal of this work was to develop an innovative and automated, non-destructive method to assess... J. Tardaguila, F. Palacios, M. Diago, E.A. Moreda

4. Development of an Overhead Optical Yield Monitor for a Sugarcane Harvester in Louisiana

A yield monitor is a device used to measure harvested crop weight per unit area for a specific location within a field.  The device documents yield variability in harvested fields and ultimately can be used to create a geographical-referenced yield map. Yield maps can be used to identify low yielding areas where poor soil fertility, disease, or pests may adversely affect yield.  Management practices can then be adjusted to correct these issues, resulting in an increase in yields and... R.R. Price, R.M. Johnson, R.P. Viator