Published July 15, 2020
| Version v1
Software
Open
Deeplabv3+ models for the aradeepopsis pipeline
- 1. Gregor Mendel Institute of Molecular Plant Biology GmbH
- 2. Gregor Mendel Institute of Molecular Plant Biology GmbH; Ludwig-Maximilians-Universitat Munchen
Description
Transfer learning of the DeepLabv3+ model (xception backbone) for use with aradeepopsis in single- or multi-scale mode.
1_class corresponds to model A; 2_class to model B and 3_class to model C as described here
The datasets used for training are available at https://doi.org/10.5281/zenodo.3946393 and the code used for transfer learning is available on GitHub
Files
Files
(1.0 GB)
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md5:52eb51e5b62199d0e8167d28f171c990
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169.1 MB | Download |
md5:bfe74d476b5f9dee87c8af9503d2d2fe
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165.7 MB | Download |
md5:cecd65a73c3090d3b4bcd75c6b88f416
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169.1 MB | Download |
md5:add1e6dc8df75261cd0cefc9d8c398dc
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165.7 MB | Download |
md5:e3c87022467c568bf35b50c2295b26ba
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169.1 MB | Download |
md5:f308e6a748ee587af1eb31ce968cf735
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165.7 MB | Download |
Additional details
Related works
- Is supplement to
- Software: 10.5281/zenodo.3946321 (DOI)
Funding
References
- Hüther, P.; Schandry, N.; Jandrasits, K.; Bezrukov, I.; Becker, C. aradeepopsis: From images to phenotypic traits using deep transfer learning. bioRxiv, 2020, 2020.04.01.018192.
- Chen, L.-C.; Zhu, Y.; Papandreou, G.; Schroff, F.; Adam, H. Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. arXiv [cs.CV], 2018.