Hello BeagleWorld!
My name is Razvan-Andrei Stoica and I am a third year student in Electrical and Computer Engineering at Jacobs University Bremen. I have firstly heard of BeagleBoard open source initiative from my colleague Vlad Victor Ungureanu last summer. At that time, I was doing an internship at Dolby Laboratories in Nuremberg Germany. The topic of my internship was centered on streaming and capturing raw bytes over various interfaces of entry level and professional sound cards in the context of real time synchronization of test signals. Given my background, Vlad’s mention of BB open source projects drew my attention and I have since followed some of the projects ported on the BBB. Thus, I have gained a core understanding of BeagleBoard as an open source project.
Since I am graduating at the end of this year, I would like to take part in GSoC14 as I feel that this could earn me a huge benefit on the developing side. Given BeagleBoard scope I also feel that this can be complemented at the hardware and at the theoretical levels. Having read more on the current and previous project ideas of BB, I have seen that one of the Kinect project ideas in the course ECE497 on BeagleBone PRU programming of M. Yoder is repeating during consecutive years for some time now. From my perspective, the machine vision problems could be linked nicely to a core tool of machine learning algorithms based on Neural Networks. In the end, this can prove to be a general way to porting other similar problems to BeagleBone. This is just a rough idea outside the topics outlined in the section of the current GSoC of BB.
Therefore, I would like to know if this topic would be of any interest to you or should I focus my attention on the proposed topics?
Best regards,
Andrei
Hello BeagleWorld!
My name is Razvan-Andrei Stoica and I am a third year student in Electrical and Computer Engineering at Jacobs University Bremen. I have firstly heard of BeagleBoard open source initiative from my colleague Vlad Victor Ungureanu last summer. At that time, I was doing an internship at Dolby Laboratories in Nuremberg Germany. The topic of my internship was centered on streaming and capturing raw bytes over various interfaces of entry level and professional sound cards in the context of real time synchronization of test signals. Given my background, Vlad’s mention of BB open source projects drew my attention and I have since followed some of the projects ported on the BBB. Thus, I have gained a core understanding of BeagleBoard as an open source project.
Since I am graduating at the end of this year, I would like to take part in GSoC14 as I feel that this could earn me a huge benefit on the developing side. Given BeagleBoard scope I also feel that this can be complemented at the hardware and at the theoretical levels. Having read more on the current and previous project ideas of BB, I have seen that one of the Kinect project ideas in the course ECE497 on BeagleBone PRU programming of M. Yoder is repeating during consecutive years for some time now. From my perspective, the machine vision problems could be linked nicely to a core tool of machine learning algorithms based on Neural Networks. In the end, this can prove to be a general way to porting other similar problems to BeagleBone. This is just a rough idea outside the topics outlined in the section of the current GSoC of BB.
Therefore, I would like to know if this topic would be of any interest to you or should I focus my attention on the proposed topics?
I don’t know if there are any mentors involved with the project with sufficient experience in the theory to know if a library of “machine learning algorithms based on Neural Networks” would be that useful. Can you elaborate more? Are there specific experts who we could involve?