Bayesian classification of ripening stages of tomato fruit using acoustic impact and colorimeter sensor data

By A. Baltazar, J. Aranda, G. González-Aguilar. 2008

91 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/c1b6ce03718a45175d1c3197fdceb635f5ee47dc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Yudong Zhang
2. Lenan Wu

In Control and Systems Engineering

1. Yudong Zhang
2. Lenan Wu
3. Arash Bahrammirzaee
4. Ionel Nistor
5. Eva Dezsi

In Statistics and Probability

1. Yudong Zhang
2. Lenan Wu

Citations in the corpus

• Classification of Fruits Using Computer Vision and a Multiclass Support Vector Machine (2012, methodology): “[4] first applied data fusion to nondestructive image of fresh intact tomatoes, followed by a three-class Bayesian classifier.”