Classification of longan fruit bruising using visible spectroscopy

By T. Pholpho, S. Pathaveerat, P. Sirisomboon. 2011

68 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Animal Science and Zoology, Plant Science

View Paper: https://www.semanticscholar.org/paper/5715b9ea1b7ea615607fcfd1b0ddf11de256b673

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. Wouter Saeys
3. Lenan Wu

In Animal Science and Zoology

1. Yudong Zhang
2. Wouter Saeys
3. Lenan Wu

In Plant Science

1. Yudong Zhang
2. Lenan Wu

Citations in the corpus

• Non-destructive detection of blackspot in potatoes by Vis-NIR and SWIR hyperspectral imaging (2016, background): “Pholpho, Pathaveerat, and Sirisomboon (2011), studied the 400 capability of visible spectroscopy to detect bruised longan fruits.”
• Classification of Fruits Using Computer Vision and a Multiclass Support Vector Machine (2012, methodology): “[6] used visible spectroscopy for classification of non-bruised and bruised longan fruits, and combined this with principal component analysis (PCA), Partial Least Square Discriminant Analysis (PLS-DA) and Soft Independent Modeling of Class Analogy (SIMCA) to develop classification models.”