Loading...

INDOOR POSITIONING SYSTEM

GO TO INDOOR POSITIONING SYSTEM PAGE

SEE DETAILS

MICROARCHITECTURE

GO TO MICROARCHITECTURE PAGE

SEE DETAILS

INTERNET OF THINGS

GO TO IoT PAGE

SEE DETAILS

DEEP LEARNING

GO TO DEEP LEARNING PAGE

SEE DETAILS

ECE656(00) Ubiquitous Networks

▣ Lecture outline

  In this semester, we will cover two different topics: IoT and deep learning. The first part of this lecture will focus on wireless adhoc network technology that provide low energy and low latency lightweight communication for WSN (wireless sensor networks) and MANET (mobile adhoc networks). The second part of this class will focus on deep learning techniques of artificial intelligence. Recently, deep learning techniques are used not only for machine learning but also applied to other fields of information technology as well as to the other fields of engineering and science in general. We will discuss the basic concepts of deep learning such as CNN and RNN by studying the classical papers of machine learning and deep learning. Then, we move to more recent topics of deep learning such as reinforcement learning (RL) and generative adversarial networks (GAN) by reviewing the recent research papers in deep learning.

 Professor : Lynn Choi( lchoi@korea.ac.kr, Engineering Bldg, #411, 3290-3249)

 Assistant : WonJoon Son (swj8905@korea.ac.kr, Engineering Bldg, #236, 3290-3896) 

 Time(Place) : Wednesday (1-2) Online

 Textbook :
"Deep Learning: Adaptive Computation and Machine Learning", Ian Goodfellow, MIT Press, 2016 

 Reference book : A Collection of Research Papers 

 Class notice

 

1. Lecture Note 1 was updated on August 31st

 

 


▣ Lecture slide

 

1.IoT and WSN.pdf  

 

 

            



▣ Paper Presentation
 

    

 



 Reference
 

 

 



 Reading List

 

 


 project

LOGIN

SEARCH

MENU NAVIGATION