nagadomi
451ee1407f
Stop calculate the instance loss when oracle_rate=0
2016-09-11 20:59:32 +09:00
nagadomi
c89fd7249a
Add learning_rate_decay
2016-06-02 10:11:15 +09:00
nagadomi
70a2849e39
Fix missing file
2016-05-30 06:48:26 +09:00
nagadomi
68a6d4cef5
Use MSE instead of PSNR
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PSNR depends on the minibatch size and those group.
2016-04-17 02:08:38 +09:00
nagadomi
a938cd5994
Reduce draw calls
2016-04-10 23:30:23 +09:00
nagadomi
1900ac7500
Use PSNR for evaluation
2016-03-12 06:53:42 +09:00
nagadomi
aaac6ed6e5
Refactor training loop
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more shuffle
2015-11-30 17:18:52 +09:00
nagadomi
b35a9ae7d7
tuning
2015-11-03 06:10:44 +09:00
nagadomi
490eb33a6b
Minimize the weighted huber loss instead of the weighted mean square error
...
Huber loss is less sensitive to outliers(i.e. noise) in data than the squared error loss.
2015-10-31 22:05:59 +09:00
nagadomi
8dea362bed
sync from internal repo
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- Memory compression by snappy (lua-csnappy)
- Use RGB-wise Weighted MSE(R*0.299, G*0.587, B*0.114) instead of MSE
- Aggressive cropping for edge region
and some change.
2015-10-26 09:23:52 +09:00
nagadomi
2231423056
update training script
2015-05-17 14:43:07 +09:00