Semantic Segmentation of Natural and Man-Made Fruits Using a Spatial-Spectral Two-Channel-CNN for Sparse Data
U. Pestel-Schiller, Y. Yang, и J. Ostermann. 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), (сентября 2022)
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%0 Conference Paper
%1 PesYan2022
%A Pestel-Schiller, Ulrike
%A Yang, Ye
%A Ostermann, Jörn
%B 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
%D 2022
%K Segmantic Segmentation leibnizailab myown
%T Semantic Segmentation of Natural and Man-Made Fruits Using a Spatial-Spectral Two-Channel-CNN for Sparse Data
@inproceedings{PesYan2022,
added-at = {2022-12-08T15:18:27.000+0100},
author = {Pestel-Schiller, Ulrike and Yang, Ye and Ostermann, J{\"o}rn},
biburl = {https://www.bibsonomy.org/bibtex/22ce25df2e5d955b2fcadb6c23a33d86b/tntl3s},
booktitle = {12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
interhash = {3d0c8a1610615519e66d8509caf74e80},
intrahash = {2ce25df2e5d955b2fcadb6c23a33d86b},
keywords = {Segmantic Segmentation leibnizailab myown},
month = sep,
timestamp = {2022-12-08T15:18:27.000+0100},
title = {Semantic Segmentation of Natural and Man-Made Fruits Using a Spatial-Spectral Two-Channel-CNN for Sparse Data},
year = 2022
}
