HierbaNetV1: a novel feature extraction framework for deep learning-based weed identification

HierbaNetV1: a novel feature extraction framework for deep learning-based weed identification

Extracting the essential features and learning the appropriate patterns are the two core character traits of a convolution neural network (CNN). Leveraging the two traits, this research proposes a novel feature extraction framework code-named ‘HierbaNetV1’ that retrieves and learns effective feature...

Full description

Saved in:
Bibliographic Details
Main Authors: Justina Michael, Thenmozhi Manivasagam
Format: Article
Language:English
Published: PeerJ Inc. 2024-11-01
Series:PeerJ Computer Science
Subjects:
HierbaNetV1
SorghumWeedDataset_Classification
Convolutional Neural Network (CNN)
Classification
Crop-weed identification
Precision agriculture
Online Access:https://peerj.com/articles/cs-2518.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://peerj.com/articles/cs-2518.pdf

Similar Items