Hello Hassan, thanks for the update.
> There is another paper "Text to Photo-realistic Image Synthesis with Stacked > Generative Adversarial Networks" and its implementation is available. > Although, > the implementations are in python, but this will help me greatly to understand > the workflow. I already had knowledge about Bidirectional Recurrent Neural > Networks. I read the paper and did some information research for proper > understanding. I will be implementing it too. Sounds like a good plan to me. > Is it fine to work on just two modules and produce good results (State of the > Art accuracy as per the published paper)? Absolutely, let's focus on a few ideas and make them as fast/usable as possible, I think backed by reasonable results this would make a great project. > Regarding the other two projects, can you give me some advice? What else > should > I do next regarding the "Essential Deep Learning Modules"? For each project there are interesting discussions in the mailing list archive, so make sure to check the archive. See http://mlpack.org/gsoc.html for information about how to search the archive. Also, it's possible to submit multiple ideas but my recommendation is to select a single idea and focus on that one. I hope anything I said was helpful, let me know if I should clarify anything. Thanks, Marcus > On 22. Mar 2018, at 17:36, Hassan Mahmood <[email protected]> wrote: > > Hello Marcus! > I showed interest in "Essential Deep Learning Modules" project on the mailing > list. > I digged deep in the project, specifically "Stacked Generative Adversarial > Networks" and "Bidirectional Recurrent Neural Networks". > > So far, I have done the following: > I developed the understanding of mlpack code base by building it on my laptop > and used some available functionalities like mlpack_linear_regression and > mlpack_perceptron. > I went through the neural network code part (Artificial Neural Network (ann)) > in mlpack code base and I will be using those existing layers and activation > functions. > I skimmed through Kris Singh's implementation of GAN from GSOC 2017 which > will be useful while implementing Stacked GANs. I might use some of his code. > I also read the Stacked GANs paper and understood the main concept. I just > have one or two vague concepts which I am trying to understand. > There is another paper "Text to Photo-realistic Image Synthesis with Stacked > Generative Adversarial Networks" and its implementation is available. > Although, the implementations are in python, but this will help me greatly to > understand the workflow. > I already had knowledge about Bidirectional Recurrent Neural Networks. I read > the paper and did some information research for proper understanding. I will > be implementing it too. > > Besides, I am interested in "Automatic Bindings to new Languages" and "String > Processing Utilities" projects. > I am now familiar with code base and workflow for Automatic Bindings > procedure in mlpack. > > For now, I am reading and watching tutorials on SGANs and some of its > effective variants (changed hyperparameters and optimization). > > I have few questions: > Is it fine to work on just two modules and produce good results (State of the > Art accuracy as per the published paper)? > Regarding the other two projects, can you give me some advice? > What else should I do next regarding the "Essential Deep Learning Modules"? > > I have started working on my application. I will share it with you soon and I > would appreciate your feedback. > > Thanks. > > Hassan Mahmood > > On Sun, Mar 11, 2018 at 10:54 PM, Marcus Edel <[email protected] > <mailto:[email protected]>> wrote: > Hello Hassan, > > welcome and thanks for getting in touch. > >> I have implemented YOLO detector, SSD and Segnet for segmentation and have >> achieved an accuracy of 89% using YOLO and 67% using SSD in real time. >> Currently, I am working to combine Segnet for segmenting the vehicles and >> feeding them to Detection Net. > > That sounds really interesting, the capabilities of YOLO are really good, I > think you can get about 50-60 FPS on a decent GPU? > >> I have a vivid concept about the implementation of the project. I have >> worked in >> Python for implementing Convolution Neural Networks, mostly. However, I am >> proficient in C++ too. So, I am confident that I will be able to complete it >> in >> summer. >> >> I would like to have a detail discussion with you on this project. > > Please don't hesitate to ask questions about the project either over the > mailing > list or on IRC (#mlpack). > >> Regarding Variational Autoencoders project, I do not have much of the >> expertise >> in generative models but I have used MNIST dataset for learning generative >> models. I have skim through the 'Tutorial on Variational AutoEncoders' paper >> which includes the detailed mathematical explanation of the proposed model. >> My >> idea is that this project is research oriented. > > At this point we are mostly interested in the standard implementation, it > should > be possible to use the existing classes (FFN, linear layer); but I agree this > project could include a research component. > >> Please do let me know, what is expected from me, for the project proposal? >> What >> kind of skills, in particular, do I need to exhibit in my proposal? >> Suggestions >> regarding how should I proceed with the project or any alternative approach >> that >> you have in mind? > > The Application Guide > (https://github.com/mlpack/mlpack/wiki/Google-Summer-of- > <https://github.com/mlpack/mlpack/wiki/Google-Summer-of-> > Code-Application-Guide) should be useful here. > > I hope anything I said was helpfu, let me know if I should clarify anything. > > Thanks, > Marcus > >> On 8. Mar 2018, at 18:50, Hassan Mahmood <[email protected] >> <mailto:[email protected]>> wrote: >> >> Hello there, >> I am a final year Software Engineering student at National University of >> Science and Technology, Islamabad. >> For the past year, I have been working as a Research Assistant at TUKL Lab - >> SEECS, NUST on various projects related to Deep Learning, Computer Vision >> and Image Processing. >> >> Under the supervision of Dr. Faisal Shafait, a reputable professor and a >> researcher in the field of Computer Vision and Machine learning, I am >> working on Real Time Vehicle Detection and Recognition as my Senior Year >> Project. Up till now, I have implemented YOLO detector, SSD and Segnet for >> segmentation and have achieved an accuracy of 89% using YOLO and 67% using >> SSD in real time. >> Currently, I am working to combine Segnet for segmenting the vehicles and >> feeding them to Detection Net. >> >> I am writing this email to show an interest in the project "Essential Deep >> Learning Modules" for Google Summer of Code 2018. I have good expertise and >> domain knowledge of Deep Learning Models. It aligns with my research area >> and my senior year project. I feel excited about the project and have a real >> hope to work on it. >> It will greatly help me in my PhD admission and my career, too. >> >> I have a vivid concept about the implementation of the project. I have >> worked in Python for implementing Convolution Neural Networks, mostly. >> However, I am proficient in C++ too. So, I am confident that I will be able >> to complete it in summer. >> >> I would like to have a detail discussion with you on this project. >> >> I also find "Variational Autoencoders" and "String Processing Utilities" >> projects, interesting. >> >> Regarding Variational Autoencoders project, I do not have much of the >> expertise in generative models but I have used MNIST dataset for learning >> generative models. >> I have skim through the 'Tutorial on Variational AutoEncoders' paper which >> includes the detailed mathematical explanation of the proposed model. My >> idea is that this project is research oriented. >> >> Please do let me know, what is expected from me, for the project proposal? >> What kind of skills, in particular, do I need to exhibit in my proposal? >> Suggestions regarding how should I proceed with the project or any >> alternative approach that you have in mind? >> >> I would really appreciate, if you can help me out. >> >> Thank you. >> >> Regards, >> Hassan Mahmood >> Software Engineering >> NUST H-12 Islamabad >> >> _______________________________________________ >> 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> > > > > -- > Hassan Mahmood > Software Engineering > NUST H-12 Islamabad > >
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