[gdal-dev] GSOC 2016

[sarthak agarwal]

Hello Dmitry,

As you know I did submit the proposal on the GSoC portal but there has been
no discussion of any kind.
I also completed my GSoC task(fixed the bug) on time.

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.
I am really interested in applying for the program and contibuting to gdal.

Regards,
Sarthak

On Sat, Mar 26, 2016 at 12:13 AM, sarthak agarwal <sarthak0415 at gmail.com>
wrote:

> I have submitted the proposal, please check it once and provide your
> feedback.
>
> Sarthak
>
> On Fri, Mar 25, 2016 at 2:01 PM, Dmitry Baryshnikov <bishop.dev at gmail.com>
> wrote:
>
>> Hi Sarthak,
>>
>> Thank you for you note, but I already wrote:
>>
>> >    Don't wait for anybody with proposal. The new GSoC site is right
>> place to discuss proposals.
>>
>> So I expected to see and comment, if needed, your proposal on this site.
>> Let me remind you the site - https://summerofcode.withgoogle.com/
>>
>> Best regards,
>>     Dmitry
>>
>> 25.03.2016 10:17, sarthak agarwal пишет:
>>
>> The deadline is today.
>>
>> Sarthak
>>
>> On Thu, Mar 24, 2016 at 1:52 AM, sarthak agarwal <
>> <sarthak0415 at gmail.com>sarthak0415 at gmail.com> wrote:
>>
>>> Hello Dmitry,
>>>
>>> I fixed the bug (I guess).
>>> Now coming to my proposal for GSoC, So I was thinking of working on
>>> project #4 *Auto-detection of EPSG codes from incomplete WKT.*
>>>
>>> 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.
>>>
>>> The attributes can be extracted from the file for which I read this
>>> <http://www.gdal.org/osr_tutorial.html#querying_coordinate_system>.
>>>
>>> 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.
>>>
>>> The way ML will handle this problem is as follows-
>>>
>>>    1. We need to find the EPSG code for a file (testing data)
>>>    2. We have a file with some attributes (projections,datum,etc ).
>>>    3. We need to the guess the best suitable class for that file(EPSG)
>>>    4. Also, we have many files for which we know the attributes and the
>>>    corresponding class (training data).
>>>
>>> This problem is now translated into an ML problem which can be solved
>>> using the following models-
>>>
>>> 1. Bayesian Stastics
>>> <https://en.wikipedia.org/wiki/Posterior_probability>
>>>
>>> where,
>>> posteriror probability = probability of this file have EPSG code 'a'.
>>> prior probability = probability of occurence of EPSG code 'a'.
>>>
>>> likelihood probablity = cases where we saw such attributes when the EPSG
>>> code is 'a'.
>>>
>>>
>>> 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).
>>>
>>>
>>> 3. We can use multi-class SVM.
>>>
>>> 4. any other suggestion from the community regarding the possible choice
>>> of the algo.
>>>
>>> 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.
>>>
>>> Please provide me feedback on my proposal and suggestion if I can
>>> add/change anything.
>>> And since very less time is left in the deadline, I would like to
>>> convert it into proposal ASAP with your help.
>>>
>>> Regards,
>>> Sarthak
>>> ​
>>>
>>
>
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