Tree Health Assessment from UAV Images: Improving Object Detection and Classification Using Hard Negative Mining and Semi-Supervised Autoencoder

Orchard tree inventory has been an essential step to obtain up-to-date information for effective tree treatments and crop insurance purposes. Inventorying trees is often performed manually through fieldwork surveys, which are generally time-consuming, costly, and subject to errors. Motivated by the...

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Vydané v:	2023 20th Conference on Robots and Vision (CRV) s. 312 - 319
Hlavní autori:	Jemaa, Hela, Bouachir, Wassim, Leblon, Brigitte, LaRocque, Armand, Haddadi, Ata, Bouguila, Nizar
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.06.2023
Predmet:	Autoencoder Autonomous aerial vehicles DeepForest Feature extraction Hard Negative Mining (HNM) Object detection Robustness semi-supervised learning Surveys UAV Vegetation Vegetation mapping YOLO
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