<div dir="ltr"><div>Hello Dmitry,</div><div><br></div><div>As you know I did submit the proposal on the GSoC portal but there has been no discussion of any kind. </div><div>I also completed my GSoC task(fixed the bug) on time.</div><div><br></div><div>So I request you to kindly review my proposal once and provide your feedback. I will make the necessary changes or if you want to change the idea and implementation we can work on that also.</div><div>I am really interested in applying for the program and contibuting to gdal.<br></div><div><br></div><div>Regards,</div><div>Sarthak</div><div class="gmail_extra"><br><div class="gmail_quote">On Sat, Mar 26, 2016 at 12:13 AM, sarthak agarwal <span dir="ltr"><<a href="mailto:sarthak0415@gmail.com" target="_blank">sarthak0415@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr">I have submitted the proposal, please check it once and provide your feedback.<span><font color="#888888"><div><br></div><div>Sarthak</div></font></span></div><div><div><div class="gmail_extra"><br><div class="gmail_quote">On Fri, Mar 25, 2016 at 2:01 PM, Dmitry Baryshnikov <span dir="ltr"><<a href="mailto:bishop.dev@gmail.com" target="_blank">bishop.dev@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<div text="#000000" bgcolor="#FFFFFF"><span>
Hi Sarthak,<br>
<br>
Thank you for you note, but I already wrote:<br>
<br></span><span>
> Don't wait for anybody with proposal. The new GSoC site is
right place to discuss proposals.<br>
<br></span><span>
So I expected to see and comment, if needed, your proposal on this
site. Let me remind you the site - <a href="https://summerofcode.withgoogle.com/" target="_blank">https://summerofcode.withgoogle.com/</a>
<pre cols="72">Best regards,
Dmitry</pre>
<div>25.03.2016 10:17, sarthak agarwal
пишет:<br>
</div>
</span><blockquote type="cite">
<div dir="ltr">
<div class="gmail_extra">The deadline is today.</div><div><div>
<div class="gmail_extra"><br>
</div>
<div class="gmail_extra">Sarthak</div>
<div class="gmail_extra"><br>
<div class="gmail_quote">On Thu, Mar 24, 2016 at 1:52 AM,
sarthak agarwal <span dir="ltr"><<a href="mailto:sarthak0415@gmail.com" target="_blank"></a><a href="mailto:sarthak0415@gmail.com" target="_blank">sarthak0415@gmail.com</a>></span>
wrote:<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<div dir="ltr">
<div>
<p style="margin:0px 0px 1.2em!important">Hello
Dmitry,</p>
<p style="margin:0px 0px 1.2em!important">I fixed the
bug (I guess).<br>
Now coming to my proposal for GSoC, So I was
thinking of working on project #4 <b>Auto-detection
of EPSG codes from incomplete WKT.</b></p>
<p style="margin:0px 0px 1.2em!important">What I
understood from the project is that we need to
predict the EPSG code of certain files on the basis
of some attributes which are available in the file.</p>
<p style="margin:0px 0px 1.2em!important">The
attributes can be extracted from the file for which
I read <a href="http://www.gdal.org/osr_tutorial.html#querying_coordinate_system" target="_blank">this</a>.</p>
<p style="margin:0px 0px 1.2em!important">Now to solve
this problem I thought a lot of methods but I think
the best way to solve it will be using machine
learning.</p>
<p style="margin:0px 0px 1.2em!important">The way ML
will handle this problem is as follows-</p>
<ol style="margin:1.2em 0px;padding-left:2em">
<li style="margin:0.5em 0px">We need to find the
EPSG code for a file (testing data)</li>
<li style="margin:0.5em 0px">We have a file with
some attributes (projections,datum,etc ).</li>
<li style="margin:0.5em 0px">We need to the guess
the best suitable class for that file(EPSG)</li>
<li style="margin:0.5em 0px">Also, we have many
files for which we know the attributes and the
corresponding class (training data).</li>
</ol>
<p style="margin:0px 0px 1.2em!important">This problem
is now translated into an ML problem which can be
solved using the following models-</p>
<p style="margin:0px 0px 1.2em!important">1. <a href="https://en.wikipedia.org/wiki/Posterior_probability" target="_blank">Bayesian Stastics</a></p>
<div>
<blockquote style="margin:0px 0px 0px 40px;border:none;padding:0px">
<div>where,</div>
<div>posteriror probability = probability of this
file have EPSG code 'a'.</div>
<div>prior probability = probability of occurence
of EPSG code 'a'.</div>
</blockquote>
</div>
<div>
<blockquote style="margin:0px 0px 0px 40px;border:none;padding:0px">likelihood
probablity = cases where we saw such attributes
when the EPSG code is 'a'.<br>
</blockquote>
<div><br>
</div>
2. or we can use a simple knn where k is the number
of possible EPSG code and the dimension of the
feature vector is the number of possible attributes.
we need to the find a valid and promising weight
function).<br>
</div>
<p style="margin:0px 0px 1.2em!important"><br>
</p>
<p style="margin:0px 0px 1.2em!important">3. We can
use multi-class SVM.</p>
<p style="margin:0px 0px 1.2em!important">4. any other
suggestion from the community regarding the possible
choice of the algo.</p>
<p style="margin:0px 0px 1.2em!important">I am
thinking of actually implementing all these algo(may
add algo in future depending upon the suggestion)
and select the algo which gives the best performance
among all of them.</p>
<p style="margin:0px 0px 1.2em!important">Please
provide me feedback on my proposal and suggestion if
I can add/change anything.<br>
And since very less time is left in the deadline, I
would like to convert it into proposal ASAP with
your help.</p>
<p style="margin:0px 0px 1.2em!important">Regards,<br>
Sarthak</p>
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