network profile
| bio | website | www2.latech.edu/~cjohnson |
|---|---|---|
| location | Ruston, Louisiana | |
| age | 28 | |
| visits | member for | 1 year |
| seen | Apr 12 at 14:06 | |
| stats | profile views | 11 |
I am a data scientist. I am currently doing work on radar and image processing.
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Mar 21 |
comment |
How to combine the responses of two sensors? I was trying to fuse two one dimensional data sets representing "sensor response" over distance in one direction to come up with a confidence value between 0 and 1 that reflected the probability that an object of interest was present, at a given distance. The distance values are not error free, but it's as good as it's going to get. I ended up just normalizing and using an elaborate, ad hoc weighting scheme that took into account the strength of relative responses. I didn't post it as an answer, because it was totally by-gosh-by-gollied. |
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Sep 24 |
comment |
How to combine the responses of two sensors? The two sensors are the OpenCV template matching function, and the SURF algorithm. I am trying to detect certain shapes in an image. |
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Sep 21 |
comment |
How to combine the responses of two sensors? I'm a little lost. Being sensed is a binary outcome, but the response of the sensors is continuous, and I do not have an a priori threshold. I'm not sure I am comfortable interpolating a two dimensional surface from two one dimensional data sets. I think I was more curious if there were existing models for fusing data from one dimensional functions. |
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Sep 21 |
comment |
How to combine the responses of two sensors? I do not have any reference data. I'm doing a blind study. Sampling an interpolation, normalizing and then comparing the two resultant series sounds like a good idea. Thanks! |
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Sep 20 |
asked | How to combine the responses of two sensors? |
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Jun 15 |
awarded | Autobiographer |
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May 8 |
awarded | Editor |
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May 8 |
revised |
Why would someone use a Bayesian approach with a 'noninformative' improper prior instead of the classical approach? I expanded the abbreviation MCMC, to Markov chain Monte Carlo. |
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May 8 |
suggested | suggested edit on Why would someone use a Bayesian approach with a 'noninformative' improper prior instead of the classical approach? |
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Apr 26 |
awarded | Scholar |
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Apr 26 |
accepted | I have a statistic, how do I calculate its distribution? |
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Apr 26 |
comment |
I have a statistic, how do I calculate its distribution? Whammy. I was hoping that there was some kind of boot-strapping solution. Thank you for pointing out the piece-wise inversion result, I did not know about that. |
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Apr 25 |
comment |
I have a statistic, how do I calculate its distribution? Is this the only way to go about determining a distribution from a statistic? If I try to perform, $$ f_{Y}(y) = f_{X}(g^{-1}(y)) \bigl\vert \dfrac{d}{dy}g^{-1}(y) \bigr\vert, $$ any statistic $ Y = g(X) $ of the data, $ X $, involving the Spearman rank correlation test will not be one-to-one. Assuming I had a statistic, $ g(X) $, that was invertible, the underlying data, $ X $, is image data that doesn't follow any simple distributions. (I guess I could model it as a complicated mixture of Gaussians, right?) Is there any other way to describe a distribution of an arbitrary statistic? |
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Apr 25 |
awarded | Student |
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Apr 25 |
asked | I have a statistic, how do I calculate its distribution? |
