5 citations · 8 across the 8 of their papers we have counts for
3 papers · 1 filter
Enhancing the KidSat Model: Integrating Geographical Encoding and Data Quality Assessment for Childhood Poverty Prediction
Hou Hin Ip, Ka Nam Lam, Joshua Man Yu Ng +4
Accurate poverty mapping using satellite imagery is often hindered by (i) noisy and sparse survey-derived supervision, (ii) image quality issues such as cloud cover and image corru…
KidSat: satellite imagery to map childhood poverty dataset and benchmark
Makkunda Sharma, Fan Yang, Duy-Nhat Vo +6
Satellite imagery has emerged as an important tool to analyse demographic, health, and development indicators. While various deep learning models have been built for these tasks, e…
BOLLWM: A real-world dataset for bollworm pest monitoring from cotton fields in India
Jerome White, Chandan Agrawal, Anmol Ojha +3
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…