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Thu May 23 15:37:30 2019, Milind, Update, Cameras, Simulation enhancements and performance of contour detection 6x
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Sat May 25 20:29:08 2019, Milind, Update, Cameras, Simulation enhancements and performance of contour detection    
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Wed Jun 12 22:02:04 2019, Milind, Update, Cameras, Simulation enhancements  
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Mon Jun 17 14:36:13 2019, Milind, Update, Cameras, Convolutional neural networks for beam tracking
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Tue Jun 18 22:54:59 2019, Milind, Update, Cameras, Convolutional neural networks for beam tracking
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Tue Jun 25 00:25:47 2019, Milind, Update, Cameras, Convolutional neural networks for beam tracking 8x
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Tue Jun 25 22:14:10 2019, Milind, Update, Cameras, Convolutional neural networks for beam tracking
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Thu Jun 27 20:48:22 2019, Milind, Update, Cameras, Convolutional neural networks for beam tracking   
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Thu Jul 4 18:19:08 2019, Milind, Update, Cameras, Convolutional neural networks for beam tracking  
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Mon Jul 8 17:52:30 2019, Milind, Update, Cameras, Convolutional neural networks for beam tracking
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Tue Jul 9 22:13:26 2019, Milind, Update, Cameras, Convolutional neural networks for beam tracking 
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Wed Jul 10 22:32:38 2019, Milind, Update, Cameras, Convolutional neural networks for beam tracking
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Mon Jul 15 14:09:07 2019, Milind, Update, Cameras, CNN LSTM for beam tracking  
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Fri Jul 19 16:47:06 2019, Milind, Update, Cameras, CNNs for beam tracking || Analysis of results 7x
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Sat Jul 20 12:16:39 2019, gautam, Update, Cameras, CNNs for beam tracking || Analysis of results
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Sat Jul 20 14:43:45 2019, Milind, Update, Cameras, CNNs for beam tracking || Analysis of results   
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Wed Jul 24 20:05:47 2019, Milind, Update, Cameras, CNNs for beam tracking || Tales of desperation
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Thu Jul 25 00:26:47 2019, Milind, Update, Cameras, Convolutional neural networks for beam tracking 
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Mon Jun 17 22:19:04 2019, Milind, Update, Computer Scripts / Programs, PMC autolocker
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Mon Jul 1 20:18:01 2019, Milind, Update, Computer Scripts / Programs, PMC autolocker
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Tue Jul 2 12:30:44 2019, Milind, Update, Computer Scripts / Programs, PMC autolocker
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Sun Jul 7 17:54:34 2019, Milind, Update, Computer Scripts / Programs, PMC autolocker
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Tue Jun 25 23:52:37 2019, Milind, Update, Cameras, Simulation enhancements
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Mon Jul 1 20:11:34 2019, Milind, Update, Cameras, Simulation enhancements
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Message ID: 14787
Entry time: Sat Jul 20 14:43:45 2019
In reply to: 14786
Reply to this: 14807
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Author: |
Milind |
Type: |
Update |
Category: |
Cameras |
Subject: |
CNNs for beam tracking || Analysis of results |
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<Adding details>
See Attachment #2.
Quote: |
Make the MSE a subplot on the same axes as the time series for easier interpretation.
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Training dataset:
- Peak to peak amplitue in physical units: ?
- Dither frequency: 0.2 Hz
- Video data: zoomed in video of the beam spot obtained from GigE camera 198.162.113.153 at 500us exposure time. Each frame has a resolution of 640 x 480 which I have cropped to 350 x 350. Attachment #1 is one such frame.
- Yes, therefore I am going to obtain video at lower amplitudes. I think that should help me avoid the problem of not-nominal-maximum value?
- Other details of the training dataset:
- Dataset created from four vides of duration ~ 30, 60, 60, 60 s at 25 FPS.
- 4032 training data points
- Input (one example/ data point): 10 successive frames stacked to form a 3D volume of shape 350 x 350 x 10
- Output (2 dimensional vector): QPD readings (C1:IOO-MC_TRANS_PIT_ERR, C1:IOO-MC_TRANS_YAW_ERR)
- Pre-processing: none
- Shuffling: Dataset was shuffled before every epoch
- No thresholding: Binary images are gonna be of little use if the expectation is that the network will learn to interpret intensity variations of pixels.
Do I need to provide any more details here?
Quote |
Describe the training dataset - what is the pk-to-pk amplitude of the beam spot motion you are using for training in physical units? What was the frequency of the dither applied? Is this using a zoomed-in view of the spot or a zoomed out one with the OSEMs in it? If the excursion is large, and you are moving the spot by dithering MC2, the WFS servos may not have time to adjust the cavity alignment to the nominal maximum value.
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?
Quote: |
What is the minimum detectable motion given the CCD resolution?
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see attachment #4.
Quote: |
- Please upload a cartoon of the network architecture for easier visualization. What is the algorithm we are using? Is the approach the same as using the bright point scatterers to signal the beam spot motion that Gabriele demonstrated successfully
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I wrote what I think is a handy script to observe if the frames are saturated. I thought this might be handy for if/when I collect data with higher exposure times. I assumed there was no saturation in the images because I'd set the exposure value to something low. I thought it'd be useful to just verify that. Attachment #3 has log scale on the x axis.
Quote: |
What is the significance of Attachment #6? I think the x-axis of that plot should also be log-scaled.
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Quote: |
- Is the performance of the network still good if you feed it a time-shuffled test dataset? i.e. you have (pictures,Xcoord,Ycoord) tuples, which don't necessarily have to be given to the network in a time-ordered sequence in order to predict the beam spot position (unless the network is somehow using the past beam position to predict the new beam position).
- Is the time-sync problem Koji raised limiting this approach?
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