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cnn-soiltextureclassification

1-dimensional convolutional neural networks (CNN) for the classification of soil texture based on hyperspectral data

https://github.com/felixriese/cnn-soiltextureclassification

Science Score: 77.0%

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    CITATION.cff file
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    Found 23 DOI reference(s) in README
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    Links to: arxiv.org, zenodo.org
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    Low similarity (10.9%) to scientific vocabulary

Keywords

1d-cnn classification cnn conference convolutional-neural-networks hyperspectral-data publication publication-code soil-texture-classification
Last synced: 4 months ago · JSON representation ·

Repository

1-dimensional convolutional neural networks (CNN) for the classification of soil texture based on hyperspectral data

Basic Info
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  • Stars: 60
  • Watchers: 4
  • Forks: 16
  • Open Issues: 0
  • Releases: 6
Topics
1d-cnn classification cnn conference convolutional-neural-networks hyperspectral-data publication publication-code soil-texture-classification
Created almost 7 years ago · Last pushed over 3 years ago
Metadata Files
Readme License Citation

README.md

Build Status codecov Codacy Badge Paper License: MIT

CNN Soil Texture Classification

1-dimensional convolutional neural networks (CNN) for the classification of soil texture based on hyperspectral data.

Description

We present 1-dimensional (1D) convolutional neural networks (CNN) for the classification of soil texture based on hyperspectral data. The following CNN models are included:

These 1D CNNs are optimized for the soil texture classification based on the hyperspectral data of the Land Use/Cover Area Frame Survey (LUCAS) topsoil dataset. It is available here. For more information have a look in our publication (see below).

Introducing paper: arXiv:1901.04846

Licence: MIT

Authors:

Citation of the code and the paper: see below and in the bibtex file

Requirements

Setup

```bash git clone https://github.com/felixriese/CNN-SoilTextureClassification.git

cd CNN-SoilTextureClassification/

wget https://raw.githubusercontent.com/titu1994/keras-coordconv/c045e3f1ff7dabd4060f515e4b900263eddf1723/coord.py . ```

Usage

You can import the Keras models like that:

```python import cnn_models as cnn

model = cnn.getKerasModel("LucasCNN") model.compile(...)

```

Example code is given in the lucas_classification.py. You can use it like that:

```python from lucasclassification import lucasclassification

score = lucasclassification( data=[Xtrain, Xval, ytrain, yval], modelname="LucasCNN", batchsize=32, epochs=200, randomstate=42)

print(score) ```

Citation

[1] F. M. Riese, "CNN Soil Texture Classification", DOI:10.5281/zenodo.2540718, 2019.

DOI

tex @misc{riese2019cnn, author = {Riese, Felix~M.}, title = {{CNN Soil Texture Classification}}, year = {2019}, publisher = {Zenodo}, DOI = {10.5281/zenodo.2540718}, }

Code is Supplementary Material to

[2] F. M. Riese and S. Keller, "Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data", ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. IV-2/W5, pp. 615-621, 2019. DOI:10.5194/isprs-annals-IV-2-W5-615-2019

tex @article{riese2019soil, author = {Riese, Felix~M. and Keller, Sina}, title = {Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data}, year = {2019}, journal = {ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences}, volume = {IV-2/W5}, pages = {615--621}, doi = {10.5194/isprs-annals-IV-2-W5-615-2019}, }

[3] F. M. Riese, "LUCAS Soil Texture Processing Scripts," Zenodo, 2020. DOI:0.5281/zenodo.3871431

[4] Felix M. Riese. "Development and Applications of Machine Learning Methods for Hyperspectral Data." PhD thesis. Karlsruhe, Germany: Karlsruhe Institute of Technology (KIT), 2020. DOI:10.5445/IR/1000120067

Owner

  • Name: Dr. Felix Riese
  • Login: felixriese
  • Kind: user
  • Location: Munich, Germany
  • Company: @Peter-Park-Systems-GmbH

Ph.D. & MBA | Head of Product | Physicist with 9+ Years in Data Science and Machine Learning | First-Principles Thinking

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite both the article from preferred-citation and the software itself."
authors:
  - family-names: Riese
    given-names: Felix M.
    orcid: https://orcid.org/0000-0003-0596-9585
title: "CNN Soil Texture Classification"
version: 1.1
doi: "10.5281/zenodo.2540718"
date-released: 2020-06-09
repository-code: https://github.com/felixriese/CNN-SoilTextureClassification
license: MIT
preferred-citation:
  authors:
    - family-names: Riese
      given-names: Felix M.
    - family-names: Keller
      given-names: Sina
  title: "Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data"
  type: article
  year: 2019
  doi: "10.5194/isprs-annals-IV-2-W5-615-2019"
  journal: "ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences"
  volume: IV-2/W5
  url: https://www.mdpi.com/2072-4292/12/1/7
  pages: "615-621"

GitHub Events

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  • Watch event: 3
  • Fork event: 1
Last Year
  • Watch event: 3
  • Fork event: 1

Committers

Last synced: 5 months ago

All Time
  • Total Commits: 40
  • Total Committers: 2
  • Avg Commits per committer: 20.0
  • Development Distribution Score (DDS): 0.3
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Felix Riese f****e@k****u 28
Felix M. Riese m****l@f****e 12
Committer Domains (Top 20 + Academic)
felixriese.de: 1 kit.edu: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 1
  • Total pull requests: 2
  • Average time to close issues: over 1 year
  • Average time to close pull requests: 7 minutes
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 3.0
  • Average comments per pull request: 0.5
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
Issue Authors
  • wellescastro (1)
Pull Request Authors
  • felixriese (2)
Top Labels
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enhancement (1)
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Packages

  • Total packages: 2
  • Total downloads: unknown
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 0
    (may contain duplicates)
  • Total versions: 10
proxy.golang.org: github.com/felixriese/cnn-soiltextureclassification
  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 4 months ago
proxy.golang.org: github.com/felixriese/CNN-SoilTextureClassification
  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 4 months ago

Dependencies

requirements.txt pypi
  • codecov *
  • matplotlib *
  • pydot *
  • pytest >=6.0.0
  • pytest-cov *
  • requests *
  • scikit-learn *
  • seaborn *
  • tensorflow >=2.5.0