Fast and Compact Model for Palm Bunch Classification Using DT-CWT and LSTM on Hue Histogram-Reference-Cited by-同舟云学术

Fast and Compact Model for Palm Bunch Classification Using DT-CWT and LSTM on Hue Histogram

Published:2023 Issue: Volume:11 Page:141445-141455
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Pipitsunthonsan Pronthep¹^ORCID,Khaorapapong Thanate¹,Nakasathien Sutkhet²,Suriyachai Petcharat¹,Channumsin Sittiporn³^ORCID,Chongcheawchamnan Mitchai¹^ORCID

Affiliation:

1. Faculty of Engineering, Prince of Songkla University, Songkhla, Thailand

2. Faculty of Agriculture, Kasetsart University, Bangkok, Thailand

3. Space Technology Research Center, Geo-Informatics and Space Technology Development Agency (GISTDA), Bangkok, Thailand

Funder

Royal Golden Jubilee Ph.D.-Thailand

Agriculture Food and Biotechnology Project of in subproject “In-field application of oil palm bunch inspector system” Kasetsart University (KU), Thailand

Prince of Songkla University (PSU), Thailand

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10332169.pdf?arnumber=10332169

Reference37 articles.

1. Oil palm fresh fruit bunch ripeness classification on mobile devices using deep learning approaches

2. Image-based processing for ripeness classification of oil palm fruit

3. Machine vision for the maturity classification of oil palm fresh fruit bunches based on color and texture features

4. Intelligent Color Vision System for Ripeness Classification of Oil Palm Fresh Fruit Bunch

5. Model-based classification of tomato fruit development and ripening related to physiological maturity