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CNN Feature Based Graph Convolutional Network For Weed and Crop Recognition in Smart Farming by Akash Agnihotri is a document available to read on EtoBox.

The document presents a CNN feature-based graph convolutional network (GCN) approach for weed and crop recognition in smart farming, achieving high accuracy with limited labeled data. The proposed method utilizes semi-supervised learning to enhance recognition performance, outperforming existing techniques on multiple datasets. The study demonstrates the effectiveness of the GCN-ResNet-101 model, achieving recognition accuracies above 96% across four datasets, and provides publicly available datasets and so

Author

Akash Agnihotri

Language

EN