Back to Search Start Over

BOLLWM: A real-world dataset for bollworm pest monitoring from cotton fields in India

Authors :
White, Jerome
Agrawal, Chandan
Ojha, Anmol
Agnihotri, Apoorv
Sharma, Makkunda
Doshi, Jigar
Source :
ICLR 2023 workshop on Practical Machine Learning for Developing Countries
Publication Year :
2023

Abstract

This paper presents a dataset of agricultural pest images captured over five years by thousands of small holder farmers and farming extension workers across India. The dataset has been used to support a mobile application that relies on artificial intelligence to assist farmers with pest management decisions. Creation came from a mix of organized data collection, and from mobile application usage that was less controlled. This makes the dataset unique within the pest detection community, exhibiting a number of characteristics that place it closer to other non-agricultural objected detection datasets. This not only makes the dataset applicable to future pest management applications, it opens the door for a wide variety of other research agendas.

Details

Database :
arXiv
Journal :
ICLR 2023 workshop on Practical Machine Learning for Developing Countries
Publication Type :
Report
Accession number :
edsarx.2304.00763
Document Type :
Working Paper