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→‎Multimedia Resource Allocation for QoE Improvement by Deep Learning

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 === Multimedia Resource Allocation for QoE Improvement by Deep Learning===
-* '''New!''' Deep learning has been widely used in various real-time applications and systems. Dynamic resource allocation for multimedia (e.g. Video) to improve QoE is an interesting topic.  We need two students for this topic.  We expect you have a background in deep learning and computer network, as well as programming skills like Python and Go.
+* '''New!''' Deep learning has been widely used in various real-time applications and systems. Dynamic resource allocation for multimedia (e.g. Video) to improve QoE is an interesting topic.  We need three students for this topic.  We expect you have a background in deep learning and computer network, as well as programming skills like Python and Go.
 (1) one to realize and improve the system for video transmission and network configuration according to resource allocation policy;
 * You will use QUIC [https://github.com/lucas-clemente/quic-go] protocol (Go language) to implement network allocation and place the server part on AWS/other clouds.
+(2) one to implement the deep learning algorithm to design the controller for dynamic resource allocations.
-(2) another one to implement the deep learning algorithm to design the controller for dynamic resource allocations to improve QoE.
+(3) one student for the QoE model using deep learning.
 Please contact  Dr.Tingting Yuan [tingting.yuan@cs.uni-goettingen.de ] and Weijun Wang [weijun.wang@informatik.uni-goettingen.de](B/M/P)
 === Low Power, Wide Area (LPWA) technologies on smart cities===