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I'm currently learning to use SymPy. It seems interesting and useful, but I haven't had much luck finding out what it's used for in the "real-world".
What scientific/industrial/academic projects are using SymPy?
For some of the uses in academia, you can check the SymPy Papers page on the SymPy Wiki. The quantum papers in particular use SymPy a lot, mostly because SymPy is used in a quantum physics course on Cal Poly (the professor teaching the course is also a major contributor to SymPy). You can also find some random projects using SymPy with Google Code Search, but I couldn't identify any major projects.
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I have been working on IMU sensors to get orientation and I am looking for an open source EKF filter! Or please share ur expertise if anyone has experience!
I took on the same task this summer with a flight-path interpreter. Check out my implementation of the linear filter here.
It looks like researchers believe the EKF yields less reliable estimates without some complicated mitagtion techniques. For measurement that are changing very rapidly (unlike GPS navigation where EKF is indeed a de facto standard), consider avoiding the EKF. According to that paper, the ongoing-estimate can diverge pretty quickly.
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For a more complex project, I need to compute the approximate, relative distances of objects from two images (from stereo-cameras). Practically what this neat tutorial explains: https://chrisjmccormick.wordpress.com/2014/01/10/stereo-vision-tutorial-part-i/ and with a result like that
Think I shouldn't be reinventing the wheel for this project and since speed is very important (realtime from two videostreams) I'm looking for a native library (preferably in C++ where the whole project is written in) for this task.
Does anyone have a suggestion?
Open source would be greatest but not mandatory.
Huge thanks in advance!
try with LIBELAS library (Library for Efficient Large-scale Stereo Matching).
Best!
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I would like to implement object detection using Caffe framework and Convolution Neural Network, could you recommend some papers and demos about that?
I just need to know how to implement it.
If you can provide the source code, it will be perfect.
A very good starting point to object detection using Deep Learning is the series of papers on R-CNN by Ross Girshick.
You can find python impelementation of faster R-CNN a good reference for implementation.
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I am trying to implement a graphing calculator on the iPhone. I am looking for a library that can take strings of expressions or functions and let me manipulate them (find derivatives, intercepts, zeros, etc). Does anything like this exist?
There's GiNaC for C++. GPL-licensed and actively maintained, last update only a month ago. I found old links to many others that don't seem to exist anymore; perhaps people simply found it easier to use GiNaC?
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I am looking for a C++ library, and I am dealing with convex objective and constraint functions.
I am guessing your problem is non-linear. Where i work, we use SNOPT, Ipopt and another proprietary solver (not for sale). We have also tried and heard good things about Knitro.
As long as your problem is convex, all these solvers work well.
They all have their own API, but they all ask for the same information : values, first and second derivatives.
Assuming your problems are nonlinear, you can use free and open-sourced OPT++, available from Sandia Lab. I have used it in one project in C++ and it was easy to use and worked well.
From what I know, the CPLEX solver is the best convex optimization solver. Its the state of the art in LP solvers. Does convex optimization really well. While looking for it, I see that its IBM's software now. You can find it here : http://www-01.ibm.com/software/integration/optimization/cplex/