Automatic Panicle detection in unmanned aerial vehicle images using TSDPC

Author(s):

M. Peiro Hosseini Nejad , A. Karami*

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

Panicle counts (PC) provide valuable information about yield prediction in sorghum but are expensive and time-consuming to acquire via traditional manual approaches. In this thesis, high-resolution RGB imagery acquired by UAVs has been used. The proposed method based on task-aware spatial disentanglement (TSD) has been modified to improve the performance of panicle detection. TSDPC has high accuracy in comparison to state-of-the-art techniques such as CenterNet and RepPoints.

Keywords:

Deep Learning , UAV Images , Panicle Counting , Small Objects

Language:
Persian
Published:
Journal of Geomatics Science and Technology, Volume:11 Issue: 4, 2022
Pages:
1 to 10
https://magiran.com/p2456136