A Novel Automated Cloud-Based Image Datasets for High Throughput Phenotyping in Weed Identification.

Published: 11 November 2024| Version 3 | DOI: 10.17632/hs7d7kpd3z.3
Contributors:
Sunil G C, Cengiz Koparan, Arjun Upadhyay, Mohammed Raju Ahmed, Yu Zhang, Kirk Howatt, Xin Sun

Description

A greenhouse-based automatic data acquisition system generated a dataset encompassing six weed species and eight crop varieties. The dataset has been made publicly accessible to facilitate advancements in weed and crop detection research utilizing computer vision and AI techniques. If you want to used this data please cite our paper G C, S., Koparan, C., Upadhyay, A., Ahmed, M. R., Zhang, Y., Howatt, K., and Sun, X. (2024). A Novel Automated Cloud-Based Image Datasets for High Throughput Phenotyping in Weed Classification. Data in Brief .

Files

Steps to reproduce

Please refer to the paper on how the dataset was obtained and preprocessed. Paper : G C, S., Koparan, C., Upadhyay, A., Ahmed, M. R., Zhang, Y., Howatt, K., and Sun, X. (2024). A Novel Automated Cloud-Based Image Datasets for High Throughput Phenotyping in Weed Classification. Data in Brief .

Institutions

North Dakota State University

Categories

Greenhouse Crops, Weed

Funding

National Institute of Food and Agriculture

ND01487

U.S. Department of Agriculture

58-6064-8-023

Licence