The IEEE Kolkata GRSS Chapter  in association Center for Soft Computing Research, Indian Statistical Institute, Kolkata will be organizing an International School on Deep Learning in SAR and Hyperspectral Remote Sensing during October 29-November 2, 2018.

In recent times, machine learning techniques are used in varieties of problem in science and engineering where typical statistical or physics oriented approaches are inefficient to handle complex and large data. The ‘Big data’ issue in remote sensing is not only limited to the enormous sizes of data generated by hyperspectral or SAR techniques, but also due to increased number of features (or bands). Moreover, the analysis of images obtained through such techniques is challenging due to the presence of noise, shadow and multiple scattering effects. Polarimetric SAR and hyperspectral remote sensing are increasingly becoming popular due to improved resolution and wide applications. It is imperative to increase trained manpower on this topic to address the potential problems. India is one of the leading countries in gathering remote sensing data from its own space program under the aegis of ISRO. The volume and variety of remote sensing
data increased exponentially with the launch of varied sensors from ISRO, NASA, ESA etc. This makes remote sensing data an ideal candidate for Big data applications due to its sheer volume and varieties in terms of temporal, spatial and spectral resolution, continuous collection of data (velocity) and necessity of ground validation (veracity). Many scientists in India are actively involved with remote sensing data analysis ranging from SAR data to microwave to optical. Through this school, we envision to expand the outreach of the ongoing activities with eminent scientists from other parts of the globe.

The aim of this school is to gather experts in Remote sensing, Data Science and Machine Learning, and facilitate the participants to get both theoretical and hands-on experience on different aspects of this subject. The school will provide a forum for exchanging ideas and information on current research studies, challenges, system developments, and practical experiences in the emerging field of Data Science and Machine Learning dedicated for remotely sensed data.
During this 5-days long school, a few small groups of participants will be formed under the mentorship of an expert. Each group will contribute to solve a specific problem in this domain.

Target participants are Masters/ Ph.D students and early career researchers from all over the world. Limited support to students for travel and accommodation will be provided.

Faculty and  Topic

 

• B. S Dayasagar, ISI Bangalore:                                                                   Remote Sensing Image analysis
• Avik Bhattacharya, IIT Bombay :                                                               SAR Image Processing
• Sonali Agarwal, IIIT Allahabad :                                                      Hyper-Spectral Image Processing
• Ashish Ghosh, ISI, Kolkata :                                                                          Deep Learning
• Saurabh Das, IIT Indore :                                                                              Remote Sensing

Special Lecture

Prof. William Blackwell, MIT Lincoln Lab: Overview of the NASA TROPICS CubeSat Constellation Mission

Venue:

Seminar Room,
Center for Soft Computing Research,
1st Floor, R. A. Fisher Bhawan,
Indian Statistical Institute,
203 B. T. Road, Kolkata 700 108, India.

Registration fee details:

Student (Masters, Ph.D., Post-doc)

• Indian Participants Rs. 7000/-
• Foreign Participants US$ 700

Faculty

• Indian Participants Rs. 10000/-
• Foreign Participants US$ 1000

(Registration fee includes Kits, learning materials and working lunch)

How to Apply

Important Information

• Number of seats is limited to 50.
• Last date of receipt of application is 10 September 2018.  15 October 2018 (Extended Deadline)
• Tentative list of selected participants will be displayed on the website from 20 September 2018.
• Last date of receipt of application fee is 23 October 2018.
• Applicants are requested to visit the website for regular updates about the workshop.

To Download Call for Participation, click here.

Registration form: click here

Updated list of accepted participants: click here  

Fee payment details

Schedule: click here