Hello Marcus, thank you for the suggestions!
At this time both architectures (RCNN and R-CNN) seem interesting to me. For my first proposition - RCNN I have knowledge and experience in implementing this architecture, so it should be easier to prepare my implementation proposal. For the second architecture - R-CNN I think I need to read some articles to have better understanding. I will read [1], [2] and [3] for the weekend and I will start thinking about the implementation. I will let know after weekend if I have some questions and concerns. Thanks, Ewelina ------------------------------------------------------------ [1] https://arxiv.org/pdf/1311.2524v5.pdf [2] https://arxiv.org/pdf/1504.08083.pdf [3] https://arxiv.org/pdf/1506.01497v3.pdf 2018-03-07 21:56 GMT+01:00 Marcus Edel <[email protected]>: > Hello Ewelina, > > welcome and thanks for getting in touch. > > My name is Ewelina Nowak and I am 2nd-year student of Computer Science at > Gdansk > University of Technology, Poland. I have experience in ML area, for > example: > measuring heart-rate with EEG signals using several ML techniques > (publication), > recognition and classification music mood in real-time (thesis from my > first > field of study), drone detection using camera and microphone arrays > (projects > done at my internships). I am currently at internship at Intel Nervana > which > helps develop my skills and experience in the AI area. > > > Sounds like you already looked into some really interesting areas. > > Could you please give me more information if any of proposed architectures > can > be interesting and useful in mlpack? I would be very grateful for any help > and > hints. > > > Each idea is definitely interesting and would fit into the existing > codebase, my > recommendation at this point is to focus on one or two ideas. (BRNN isn't > enough > for the summer as a single project, but this would be a neat addition). > > Let me know if I should clarify anything. > > Thanks, > Marcus > > On 7. Mar 2018, at 16:53, Ewelina Nowak <[email protected]> > wrote: > > Hello > > > My name is Ewelina Nowak and I am 2nd-year student of Computer Science at > Gdansk University of Technology, Poland. I have experience in ML area, for > example: measuring heart-rate with EEG signals using several ML techniques > (publication), recognition and classification music mood in real-time > (thesis from my first field of study), drone detection using camera and > microphone arrays (projects done at my internships). I am currently at > internship at Intel Nervana which helps develop my skills and experience in > the AI area. > > Recently, I have started to familiarize myself with mlpack code. I > downloaded mlpack, compiled it from source and set up a development > environment. Currently I am reading mlpack tutorials and I try to > experiment with some mlpack ML implementations to get better understanding > of the project. > > I am interested in participating in GSoC 2018 and I am particularly > interested in Essential Deep Learning Modules. After reading proposed > papers and after doing some research I have three propositions for ANN > architectures in which I am interested: > > 1. RCNN (Recurrent Convolutional Neural Networks): I have an experience in > using RNN (with LSTM and GRU units) with CNN in one of my projects: Music > mood classification using deep learning modules. I used images from > spectral analysis for predicting mood of a song in time. > > 2. R-CNN (Regional based Convolutional Neural Networks): This architecture > can be used for object detection and classification. It can be used for > modern modifications of R-CNN: Fast R-CNN, Faster R-CNN or for example Mask > R-CNN. > > 3. BRNN (Bidirectional Recurrent Neural Networks): As I previously > mentioned I have experience in Recurrent Neural Networks and I would be > interested in implementing BRNN for one of my new projects in text analysis > area. > > Could you please give me more information if any of proposed architectures > can be interesting and useful in mlpack? I would be very grateful for any > help and hints. > > > Best wishes, > > Ewelina Nowak > > _______________________________________________ > mlpack mailing list > [email protected] > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack > > >
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