A Lightweight Deep Learning Model for Identifying Weeds in Corn and Soybean Using Quantization-Reference-Cited by-同舟云学术

A Lightweight Deep Learning Model for Identifying Weeds in Corn and Soybean Using Quantization

Published:2023-11-02 Issue: Volume:37 Page:318
ISSN:
Container-title:The 4th International Electronic Conference on Applied Sciences
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Author:

Aaron Alex¹,Hassan Muhammad²,Hamada Mohamed³^ORCID,Kakudi Habiba¹

Affiliation:

1. Department of Computer Science, Bayero University, Kano 700006, Nigeria

2. Department of Software Engineering, Bayero University, Kano 700006, Nigeria

3. Software Engineering Lab, University of Aizu, Aizu-Wakamatsu 965-8580, Fukushima, Japan

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/56/1/318/pdf

Reference9 articles.

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5. Anwar, S., Hwang, K., and Sung, W. (2015, January 19–24). Fixed point optimization of deep convolutional neural networks for object recognition. Proceedings of the ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing—Proceedings, South Brisbane, QLD, Australia.

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1. Weed Recognition at Soybean Seedling Stage Based on YOLOV8nGP + NExG Algorithm;Agronomy;2024-03-24