A Hybrid Model for Soybean Yield Prediction Integrating Convolutional Neural Networks, Recurrent Neural Networks, and Graph Convolutional Networks
Soybean yield prediction is one of the most critical activities for increasing agricultural productivity and ensuring food security. Traditional models often underestimate yields because of limitations associated with single data sources and simplistic model architectures. These prevent complex, mul...
Saved in:
| Main Authors: | Vikram S. Ingole, Ujwala A. Kshirsagar, Vikash Singh, Manish Varun Yadav, Bipin Krishna, Roshan Kumar |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Computation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-3197/13/1/4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Dysarthria Severity detection Using Recurrent and Convolutional Neural Networks
by: Amina Hamza, et al.
Published: (2024-12-01) -
Klasifikasi Kualitas Biji Kedelai Menggunakan Transfer Learning Convolutional Neural Network Dan SMOTE
by: Amanda Prawita Ningrum, et al.
Published: (2024-12-01) -
Feature recommendation strategy for graph convolutional network
by: Jisheng Qin, et al.
Published: (2022-12-01) -
Copy-Move Forgery Detection Technique Using Graph Convolutional Networks Feature Extraction
by: Varun Shinde, et al.
Published: (2024-01-01) -
Rumor detection using dual embeddings and text-based graph convolutional network
by: Barsha Pattanaik, et al.
Published: (2024-11-01)