Development of ANN based Efficient Fruit Recognition Technique

Bhanu Pratap; Navneet Agarwal; Sunil Joshi

Development of ANN based Efficient Fruit Recognition Technique

Bhanu Pratap * §

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Navneet Agarwal §

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Sunil Joshi ‡

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§ College of technology and Engineering and udaipur

‡ College of Technology and Engineering, MPUAT, Udaipu...

Development of ANN based Efficient Fruit Recognition Technique

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References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Bhanu Pratap, Navneet Agarwal, Sunil Joshi. 2014. "Development of ANN based Efficient Fruit Recognition Technique". Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 14 (GJCST Volume 14 Issue C5).

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GJCST Volume 14 Issue C5

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Artificial Neural Network color fruit classification gray level co-occurrence matrix texture

Classification

I.7.5

Submission ReceivedDecember 6, 2013
Peer Review Double Blind
Handling Editor
Accepted January 2, 2014
Published July 28, 2014

Version of record

v1.2

Issue date

July 28, 2014

Language

English

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Article Matrices

Total Score: 104

Country: India

Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering

Authors: Bhanu Pratap, Navneet Agarwal, Sunil Joshi, Suriti Gupta (PhD/Dr. count: 0)

View Count (all-time): 492

Total Views (Real + Logic): 3344

Total Downloads (simulated): 285

Publish Date: 2014 01, Wed

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Total Views: 3.3K

Total Downloads: 285

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