1. Summer Research Program: Challenging to detect fish (tuna) by object detection

Tokyo University of Marine Science and Technology Marine AI Development and Evaluation Center

1.1. What you need to complete this course

  • PC

  • Google account

  • Basic knowledge of statistics and mathematics: mean and variance, sanpling, table data, scatter plot, differentiation, matrices

1.2. Preparation materials

In this course, we use Google Colaboratory as the runtime environment. The following video 1 explains how to use Colaboratory. 2 and 3 are basic content about how to use Python and Numpy, so please watch them if you are unsure. Please note that these preparatory videos are in Japanese, but English subtitles are provided.

  1. How to use Colaboratory:   video (17 min)

  2. introduction to Python: video (31 min)

  3. Introduction to NumPy: video (18 min)

1.3. Lecture Videos

These are the main contents of this course. Please watch them together with this web page you are viewing. There is a link to a Jupyter notebook for exercises at the beginning of each section, so please be sure to try the exercises.

  1. Introduction to deep learning (21 min)

  2. Introduction to PyTorch (29 in)

  3. Transfer learning of Faster RCNN object recognition model using TorchVision (27 min)