Machine Learning
Lecturer: Prof. Marcello Pelillo
Platform: ZOOM Meeting
Class time: 08:00AM-11:00AM, August 24-31, 2020 (CEST)
Course description: The course aims to provide an introduction to modern machine learning principles and algorithms and to describe their applications to selected problems in computer vision.
Course objectives: Upon successful completion of this short course, students should understand the fundamental theory and methodologies of machine learning.
Course outline:
1. Introduction to machine learning
2. Neural networks and deep learning
3. Support vector machines
4. Graph-based clustering
5. Selected computer vision applications
Social Sensing, Geospatial Big Data Computing, and Disaster Management
Lecturer: Prof. Zhenlong Li
Platform: ZOOM Meeting
Class time: 08:00PM-11:00PM, August 24-31, 2020 (EDT)
Course description: The course aims to provide an introduction to modern machine learning principles and algorithms and to describe their applications to selected problems in computer vision.
Course objectives: Upon successful completion of this short course, students should understand the fundamental theory and methodologies of machine learning.
Course outline:
1. Introduction to machine learning
2. Neural networks and deep learning
3. Support vector machines
4. Graph-based clustering
5. Selected computer vision applications
Night-time Light Remote Sensing
Lecturer: Prof. Deren Li, Prof.Xi Li, Prof. Xiaolin Zhu, Prof. Xi Chen
Platform: ZOOM Meeting
Class time: 19:00PM-22:00PM, August 24-31, 2020 (CST)
Course description. The course aims to introduce night-time light remote sensing (NLRS), including its concept, methodology, applications and future development.
Course objectives: The students will know how to start night-time light remote sensing for their own projects after finishing this course.
Course outline.
1. Introduction to NLRS (Prof. Deren LI, Prof. Xi Li)
2. Data acquisition and processing of NLRS images (Prof. Xi Li)
3. Advanced processing techniques for NLRS images (Prof. Xiaolin Zhu)
4. NLRS, sociology and economics (Prof. Xi Chen)
5. Non-conventional NLRS and future development of NLRS (Prof. Xi Li)
