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 <sarthak0...@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....@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 < >> <sarthak0...@gmail.com>sarthak0...@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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