:: Volume 11, Issue 4 (6-2022) ::
JGST 2022, 11(4): 1-10 Back to browse issues page
Automatic Panicle detection in unmanned aerial vehicle images using TSDPC
M. Peiro Hosseini Nejad, A. Karami *
Abstract:   (443 Views)
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.
Article number: 1
Keywords: Deep Learning, UAV Images, Panicle Counting, Small Objects
Full-Text [PDF 1259 kb]   (242 Downloads)    
Type of Study: Research | Subject: Photo&RS


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Volume 11, Issue 4 (6-2022) Back to browse issues page