Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Daniel Heins"'
Publikováno v:
Remote Sensing, Vol 15, Iss 14, p 3511 (2023)
Machine learning is frequently combined with imagery acquired from uncrewed aircraft systems (UASs) to detect invasive plants. Having prior knowledge of which machine learning algorithm will produce the most accurate results is difficult. This study
Externí odkaz:
https://doaj.org/article/074d6fdc6caa4787ace9c1f2593ebb3c
Improving Machine Learning Classifications of Phragmites australis Using Object-Based Image Analysis
Publikováno v:
Remote Sensing, Vol 15, Iss 4, p 989 (2023)
Uncrewed aircraft systems (UASs) are a popular tool when surveilling for invasive alien plants due to their high spatial and temporal resolution. This study investigated the efficacy of a UAS equipped with a three-band (i.e., red, green, blue; RGB) s
Externí odkaz:
https://doaj.org/article/612b3a688dca4c53834a017838b3d044
Publikováno v:
Remote Sensing, Vol 13, Iss 16, p 3303 (2021)
Invasive plant species are an increasing worldwide threat both ecologically and financially. Knowing the location of these invasive plant infestations is the first step in their control. Surveying for invasive Phragmites australis is particularly cha
Externí odkaz:
https://doaj.org/article/e1cb6f1ef92e45a38d622de41e99baf6
Publikováno v:
Remote Sensing, Vol 13, Iss 3303, p 3303 (2021)
Remote Sensing
Volume 13
Issue 16
Pages: 3303
Remote Sensing
Volume 13
Issue 16
Pages: 3303
Invasive plant species are an increasing worldwide threat both ecologically and financially. Knowing the location of these invasive plant infestations is the first step in their control. Surveying for invasive Phragmites australis is particularly cha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5411463ab2914f2c35ff63819b3eee71
https://doi.org/10.3390/rs13163303
https://doi.org/10.3390/rs13163303