Dynamic Color Transform Networks for Wheat Head Detection

Wheat head detection can measure wheat traits such as head density and head characteristics.Standard wheat breeding largely relies on manual observation to detect wheat heads,yielding a tedious and inefficient procedure.The emergence of affordable camera platforms provides opportunities for deploying computer vision(CV)algorithms in wheat head detection,enabling automated measurements of wheat traits.Accurate wheat head detection,however,is challenging due to the variability of observation circumstances and the uncertainty of wheat head appearances.In this work,we propose a simple but effective idea—dynamic color transform(DCT)—for accurate wheat head detection.