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Automatic Panicle detection in unmanned aerial vehicle images using TSDPC
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| M. Peiro Hosseini Nejad, A. Karami * |
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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 |
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Full-Text [PDF 1259 kb]
(242 Downloads)
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Type of Study: Research |
Subject:
Photo&RS
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