Progress for week 37 (2015)
From Robin
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== Per Wessel == | == Per Wessel == | ||
=== Budget === | === Budget === | ||
- | * Lese papers om anaylse av | + | * Lese papers om tids-serie anaylse av kjemikal sensorer |
* Kontakte og møte med Tobias Dahl hos Sintef | * Kontakte og møte med Tobias Dahl hos Sintef | ||
+ | * Finne potensielle veiledere og eller folk med kunnskap innen luft monitorering og sensoranalyse | ||
=== Accounting === | === Accounting === | ||
- | * Done 1 | + | * Skal møte Tobias Dahl fra Sintef denne uken |
- | * Done | + | * Er i dialog med NORA (Nitrous Oxide Reaserch Alliance) på nmbu (har ekspertise i tids-serie analyse av sensor data) og forurensning. |
+ | |||
+ | == Magnus Olden == | ||
+ | === Budget === | ||
+ | * Read papers on ensemble learning / stacking | ||
+ | * Finish essay | ||
+ | * Move to latex/lyx | ||
+ | * Learn more on Azure Machine Learning and SciKit Learn | ||
+ | |||
+ | === Accounting === | ||
+ | * Read papers | ||
+ | * Almost finished essay (4000 words, but still a little incoherent) | ||
+ | * Moved to lyx | ||
+ | * No decision yet on AML and ScKL | ||
+ | |||
+ | == Tomas Renaa == | ||
+ | === Budget === | ||
+ | * Read: | ||
+ | ** essays and master theses. | ||
+ | ** read more papers to gain get better grasp at direction of thesis. | ||
+ | * Look into MOCAP at Robin | ||
+ | * Migrate document to LaTeX | ||
+ | * Finish essay | ||
+ | |||
+ | === Accounting === | ||
+ | |||
+ | * Done 1.1, 1.2 | ||
+ | * Done 3 | ||
+ | |||
+ | == [[user:vegardli|Vegard]] == | ||
+ | === Budget === | ||
+ | * Read example essays | ||
+ | * Finish at least half of the essay | ||
+ | * Read at least half of part two of Williams and Bizup | ||
+ | |||
+ | === Accounting === | ||
+ | * Read one example essay, skimmed the rest | ||
+ | * 6-7 pages of essay written | ||
+ | * Read the expected pages | ||
+ | |||
+ | == [[user:Eirisu|Eirik Sundet]] == | ||
+ | === Budget === | ||
+ | * Recreate the region-growing clustering algorithm for road detection, implemented on the Stanley vehicle, who won the DARPA challenge in 2005. | ||
+ | * explore good features for this task | ||
+ | |||
+ | === Accounting === | ||
+ | * I've managed to estimate a gaussian model of the road in a single image, and then estimating the distance between each pixel and the mean of the road model. | ||
+ | * I've managed to estimate a gaussian mixture model from 30 road images, with corresponding ground-truth masks. | ||
+ | * I've begun to test how well the Gray-Level Co-Occurrence Matrix (GLCM) performs texture classification, in terms of accuracy and speed. | ||
+ | * I've begun to explore some recursive algorithms for region-growth, but have not yet implemented a fully functional one. |
Current revision as of 09:11, 15 September 2015
Contents |
Student template (copy this for your entry)
Budget
- Todo 1
- Todo 2
Accounting
- Done 1
- Done 2
Per Wessel
Budget
- Lese papers om tids-serie anaylse av kjemikal sensorer
- Kontakte og møte med Tobias Dahl hos Sintef
- Finne potensielle veiledere og eller folk med kunnskap innen luft monitorering og sensoranalyse
Accounting
- Skal møte Tobias Dahl fra Sintef denne uken
- Er i dialog med NORA (Nitrous Oxide Reaserch Alliance) på nmbu (har ekspertise i tids-serie analyse av sensor data) og forurensning.
Magnus Olden
Budget
- Read papers on ensemble learning / stacking
- Finish essay
- Move to latex/lyx
- Learn more on Azure Machine Learning and SciKit Learn
Accounting
- Read papers
- Almost finished essay (4000 words, but still a little incoherent)
- Moved to lyx
- No decision yet on AML and ScKL
Tomas Renaa
Budget
- Read:
- essays and master theses.
- read more papers to gain get better grasp at direction of thesis.
- Look into MOCAP at Robin
- Migrate document to LaTeX
- Finish essay
Accounting
- Done 1.1, 1.2
- Done 3
Vegard
Budget
- Read example essays
- Finish at least half of the essay
- Read at least half of part two of Williams and Bizup
Accounting
- Read one example essay, skimmed the rest
- 6-7 pages of essay written
- Read the expected pages
Eirik Sundet
Budget
- Recreate the region-growing clustering algorithm for road detection, implemented on the Stanley vehicle, who won the DARPA challenge in 2005.
- explore good features for this task
Accounting
- I've managed to estimate a gaussian model of the road in a single image, and then estimating the distance between each pixel and the mean of the road model.
- I've managed to estimate a gaussian mixture model from 30 road images, with corresponding ground-truth masks.
- I've begun to test how well the Gray-Level Co-Occurrence Matrix (GLCM) performs texture classification, in terms of accuracy and speed.
- I've begun to explore some recursive algorithms for region-growth, but have not yet implemented a fully functional one.