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About Deep Learning For Crop Yield Prediction A Systematic Literature Review
This document summarizes a research article from the New Zealand Journal of Crop and Horticultural Science. The research article conducted a systematic literature review on the use of deep learning for crop yield prediction. It analyzed 44 primary studies selected out of an initial 456 relevant studies based on selection criteria. Key findings included that convolutional neural networks were the most common algorithm and had the best performance. However, a major challenge is the lack of large training datasets which can lead to overfitting and lower performance in practice. The review aims to provide an overview of deep learning applications in crop yield prediction and discuss current challenges to help both researchers and practitioners.
Detailed Information
| Author: | ['Sainya Karumanchi'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 27 |
| Language: | English |
| Format: | |
| Price: | FREE |
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