Progress for week 43 (2018)

From Robin

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* Autoencoder implemented. Currently training models based on this architecture
* Autoencoder implemented. Currently training models based on this architecture
* Thesis worked on
* Thesis worked on
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== Anders Rønningstad ==
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=== Budget ===
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* Finish own implementation of semi Mathematical.
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* Find out more on how to implement real mathematical optimization
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* Run simulations
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** compare results
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=== Accounting ===
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* Found a way to implement mathematical (with asumption)
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* Ran some simulations

Current revision as of 11:00, 26 October 2018

Contents

David Kolden

Budget

  • Finish essay
  • Implement working camera node

Accounting

  • 85% finished with essay

Jonas Waaler

Budget

  • Implement peak detector to clean up training data
  • Test CoordConv prinsip
  • Implement autoencoder - transfer weights and create regressor
  • Evaluate trained models

Accounting

  • Peak detector algorithm implemented
  • CoordConv tested
    • Not making any difference
  • Autoencoder implemented. Currently training models based on this architecture
  • Thesis worked on


Anders Rønningstad

Budget

  • Finish own implementation of semi Mathematical.
  • Find out more on how to implement real mathematical optimization
  • Run simulations
    • compare results

Accounting

  • Found a way to implement mathematical (with asumption)
  • Ran some simulations
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