Work

Dataset of Individual Sick Fir Detection using Computer Vision and Deep Learning

Year: 2020

Type: article

Abstract: Dataset for individual sick fir detection and classification including Orthomosaics, DSM, nDSM, ROI, annotation of sick firs, healthy firs, deciduous and treetops of 9 flying missions on 4 sites of Zao Mountain. The filenames are labelled with the number of flying mission, for example: mission 1 will have data filenames as following: Z1 is orthomosaics, Z1sickfir is annotation of sick firs, Z1healthyfir is annotation of healthy firs, Z1deciduous is annotation of deciduous. Z1treetop is annotation of treetops, Z1DEM is DSM, Z1nDEM is nDSM and Z1ROI is Region of Interest.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.4054337

Authors: Nguyen, Ha Trang, Diez, Yago, Lopez Caceres, Maximo Larry, Kentsch, Sarah, Moritake, Koma, Shu, Hase

Language: English

Topic: Remote Sensing and LiDAR Applications

Subfield: Forestry

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W3217575985

FWCI:

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Related to: 10