2014
DOI: 10.1016/j.compag.2014.05.012
|View full text |Cite
|
Sign up to set email alerts
|

Classification models of bruise and cultivar detection on the basis of hyperspectral imaging data

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
33
0

Year Published

2015
2015
2023
2023

Publication Types

Select...
7
1

Relationship

0
8

Authors

Journals

citations
Cited by 60 publications
(34 citation statements)
references
References 26 publications
1
33
0
Order By: Relevance
“…Naïve Bayes surpass SVM in research on brain tumor recognition to identify two classes of brain tumor [30]. On the other hand, SVM successfully achieves higher classification accuracy in bruise and cultivar of apple detection in agriculture product [31].…”
Section: Support Vector Machine (Svm) Is a Well Know Classifier And Hmentioning
confidence: 99%
“…Naïve Bayes surpass SVM in research on brain tumor recognition to identify two classes of brain tumor [30]. On the other hand, SVM successfully achieves higher classification accuracy in bruise and cultivar of apple detection in agriculture product [31].…”
Section: Support Vector Machine (Svm) Is a Well Know Classifier And Hmentioning
confidence: 99%
“…10,14,[42][43][44] While the majority reported quite high accuracies, it is difficult to compare these asresultsweretypicallynotreportedonthepixellevel.…”
Section: Discussionmentioning
confidence: 99%
“…Three-dimensional hyperspectral cubes, i.e., (x, y, λ), where λ is the wavelength, can be acquired using pointscan, line-scan, and area-scan methods. A hyperspectral imaging system typically consists of a CCD camera (or an InGaAs camera for the NIR region), an imaging spectroscope, a light source, a sample holding platform, a computer, and related software (Leiva-Valenzuela et al, 2014;Qin et al, 2013;Siedliska et al, 2014;Tao and Peng, 2014). Figure 2 is a schematic of a hyperspectral imaging system.…”
Section: Main Optical Technologiesmentioning
confidence: 99%
“…Hyperspectral imaging systems can be categorized into Vis/NIR imaging Pierna et al, 2012;, fluorescence imaging (Cho et al, 2013;Davis et al, 2014;Noh et al, 2007), and Raman imaging (Qin et al, 2011). The light source in a hyperspectral system can be a point source (Erkinbaev et al, 2014;Tao and Peng, 2014) or a diffuse source (Dai et al, 2014;Everard et al, 2014;Lu and Ariana, 2013;Siedliska et al, 2014). The information obtained from hyperspectral image acquisition is used for detecting internal as well as external qualities of the sample.…”
Section: Main Optical Technologiesmentioning
confidence: 99%
See 1 more Smart Citation