| Name : R-imageseg
| |
| Version : 0.5.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.5.7
| Date : 2024-06-14 11:59:19
|
| Group : Development/Libraries/Other
| Source RPM : R-imageseg-0.5.0-lp153.5.7.src.rpm
|
| Size : 3.98 MB
| |
| Packager : (none)
| |
| Summary : Deep Learning Models for Image Segmentation
|
Description :
A general-purpose workflow for image segmentation using TensorFlow
models based on the U-Net architecture by Ronneberger et al. (2015)
< arXiv:1505.04597> and the U-Net++ architecture by Zhou et al. (2018)
< arXiv:1807.10165>. We provide pre-trained models for assessing canopy
density and understory vegetation density from vegetation photos. In
addition, the package provides a workflow for easily creating model
input and model architectures for general-purpose image segmentation
based on grayscale or color images, both for binary and multi-class
image segmentation.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
