Hello Rajiv, I like the idea, but perhaps we should focus on either 1 or 2, implementing both might be difficult to get done in time. Let me know what you think.
Thanks, Marcus > On 14. Mar 2019, at 09:39, Rajiv Vaidyanathan <[email protected]> > wrote: > > Hi Marcus, > > I did some more research about the Graph Neural Networks. Since I'm new to > GNNs, I am not sure about how long it will take to implement all the > necessary layers. Hence, I thought I'll work on something which I'm already > familiar about, which is convolutional neural networks. I'm extremely > interested in working on methods used for object detection. Object detection > algorithms such as R-CNN, YOLO, etc. have become very popular due to their > speed and accuracy. I feel that it would be a great addition to the MLPack > library. > > I want to implement the following networks along with tests and > documentation: > 1. R-CNN and it's variants such as fast RCNN, Faster RCNN and Mask-R-CNN > 2. YOLO > > For their implementation, the following have to be implemented: > 1. ROI pooling > 2. Region Proposal Network > 3. Techniques: non-max suppression, intersection over union and anchor boxes > > Please let me know what you think about this. If you are fine with this idea, > I'll do more research and make a brief proposal as to what needs be precisely > done with respect to the MLPack code along with a rough timeline. > > Thanks and regards, > Rajiv > ᐧ > > On Sat, 2 Mar 2019 at 03:23, Marcus Edel <[email protected] > <mailto:[email protected]>> wrote: > Hello Rajiv, > > thanks again for the contributions. Implementing Graph Neural Networks is > quite > a challenge especially timewise but if you are up for that; we should make > sure > the timeline is reasonable including the milestones. Everything needs to be > tests and stable at the end of the summer which often takes a lot of time, but > as I said if you are up for the challenge this could be an interesting project > for sure. > > Let us know what you think. > > Thanks, > Marcus > >> On 28. Feb 2019, at 19:14, Rajiv Vaidyanathan <[email protected] >> <mailto:[email protected]>> wrote: >> >> Dear Marcus, Mikhail and Shikhar, >> >> I am N Rajiv Vaidyanathan and I'm interested in the topic "Essential Deep >> Learning Modules" in GSoC 19. >> >> Over the past month, I'm trying to get an understanding of the MLPack >> codebase by making contributions. As of now, I have implemented SPSA >> optimiser, Dice Loss function and currently working on Dense blocks. >> >> I recently read a paper on Graph Neural Networks and found it to be >> fascinating as it works very well on non-Euclidian spaces such as social >> networks and 3D images. I am interested in working on implementing this >> network along with tests and documentation. I'm also interested in improving >> the overall documentation of ann. >> >> Please let me know what you think :) >> >> Thanks and regards, >> Rajiv >> ᐧ >> _______________________________________________ >> mlpack mailing list >> [email protected] <mailto:[email protected]> >> http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack >> <http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack> > > ᐧ > _______________________________________________ > mlpack mailing list > [email protected] > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
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