Progress for week 2 (2016)

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=== Budget ===
=== Budget ===
* Meet with FFI-supervisors at Thursday for progress report, and planning further work
* Meet with FFI-supervisors at Thursday for progress report, and planning further work
-
* Finish making MatLab program for plotting the Probability Density Function (PDF) of the different features, with respect to typical elements in a scene (road, trees, sky, buildings, etc.)
+
* Continue work with feature analysis
 +
* making graphs and tables
=== Accounting ===
=== Accounting ===
-
*  
+
* Done 1, got some pointers to further development http://robin.wiki.ifi.uio.no/Bruker:Eirisu#II-Image_for_Improving_Textural_Feature-Images
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*
+
* Done 2, http://robin.wiki.ifi.uio.no/Bruker:Eirisu#Results_2
 +
* Have made some histograms.
== [[user:vegardli|Vegard]] ==
== [[user:vegardli|Vegard]] ==
=== Budget ===
=== Budget ===
* Implement map loading and cost calculation in VHDL model
* Implement map loading and cost calculation in VHDL model
 +
* Improve VHDL<->application communication (find bug that sometimes causes paths to disappear)
 +
 +
 +
== [[user:perwn|Per Nore]] ==
 +
=== Budget ===
 +
* om jeg får lisens til rapidminer, fortsette med testing av algoritmer
 +
 +
=== Accounting ===
 +
* Testet SVM og ANN/MLP
 +
* Testet Particle filtering.
 +
* Testet preprossesering av normalisering vs log vs autoscaling

Nåværende revisjon fra 19. jan 2016 kl. 12:13

Innhold

Student template (copy this for your entry)

Budget

  • Todo 1
  • Todo 2

Accounting

  • Done 1
  • Done 2

Eirik Sundet

Budget

  • Meet with FFI-supervisors at Thursday for progress report, and planning further work
  • Continue work with feature analysis
  • making graphs and tables

Accounting

Vegard

Budget

  • Implement map loading and cost calculation in VHDL model
  • Improve VHDL<->application communication (find bug that sometimes causes paths to disappear)


Per Nore

Budget

  • om jeg får lisens til rapidminer, fortsette med testing av algoritmer

Accounting

  • Testet SVM og ANN/MLP
  • Testet Particle filtering.
  • Testet preprossesering av normalisering vs log vs autoscaling
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