Courses and Books for Fresh Researchers

Taking courses and reading books are very important for fresh researchers. Here, the courses and books are suitable for the researchers who are interesting in Computer Vision, Simultaneous Localization and Mapping (SLAM), Deep Learning, Robotics, etc.

How can researchers improve themselves? Look at the figure above, researchers are “Agent”. “state” means knowledge in brains. “reward” shows achievements. “action” indicates practice. Reading books helps obtain knowledge (i.e., update “state”). At the same time, please apply the knowledge to applications (i.e., update “action”). Finally, the researchers will receive rewards, such as papers and decent jobs (i.e., update “reward”).

1. Machine Learning & Deep Learning

• Pattern Recognition and Machine Learning – Christopher M. Bishop
• Deep Learning – Ian Goodfellow, Yoshua Bengio, and Aaron Courville

2. Image Processing & Computer Vision

• Multiple View Geometry in Computer Vision – Richard Hartley, Andrew Zisserman
• Computer Vision: Algorithms and Applications – Richard Szeliski
• Digital Image Processing – Rafael C. Gonzalez, Richard E. Woods

3. SLAM

• Introduction to Visual SLAM From Theory to Practice – Xiang Gao, Tao Zhang
• SLAM in Robotics and Autonomous Driving – Xiang Gao
• STATE ESTIMATION FOR ROBOTICS – Timothy D. Barfoot

4. Motion Planning & Control

• Reinforcement Learning: An Introduction – Richard S. Sutton and Andrew G. Barto