18:36:55	 From  Thomas Wagner : These days everyone is keen to use neural networks to optimise the performance of systems with a large number of variables. Is this something you are looking to explore to refine your data acquisition or images reconstruction in parallel of CS?
18:39:35	 From  Darkphibre / Amity : Seems like any any sparse signals. Face Recognition is mentioned on the wiki, I'd imagine fingerprints may be applicable. Seems like you need a strong, sparse signal and a low noise floor?
18:39:53	 From  Darkphibre / Amity : (My take, on potential applications outside of astronomy)
18:39:53	 From  AK4GG John Phillips : Very impressive results from a non-intuitive approach for small cube sats. Is there now value in amalgamating observations from many more low cost cube sats looking at the same part of the sky ?
18:42:46	 From  Michael Kirkhart : Just found this via an online search - have only skimmed through it, but it might be helpful in trying to understand compressive sampling: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8260873
18:43:37	 From  Michael Kirkhart : This is an entirely new concept to me, but that is why I attend these conferences.
18:43:57	 From  Darkphibre / Amity : re: Phillips, It seems like it's a similar algorithm that's been used in radieo interferometry.
https://en.wikipedia.org/wiki/CLEAN_(algorithm)
18:44:09	 From  Darkphibre / Amity : Very cool IEEE paper Michael, tyvm.
18:47:44	 From  AK4GG John Phillips : Are there any special preprocessing that needs to occur with the reference plane and the spare observation planes ?
18:48:28	 From  Thomas Wagner : Quite a unique experience to watch conferences at 11pm at night from the UK :)
18:49:44	 From  Thomas Wagner : Thank you Asmita for the presentation!
18:50:03	 From  Thomas Wagner : Bye!