Summer Reseach Program, Marin AI Development and Evaluation Center, Tokyo University of Marine Science and Technology

Contents:

• 1. Summer Research Program: Challenging to detect fish (tuna) by object detection
  • 1.1. What you need to complete this course
  • 1.2. Preparation materials
  • 1.3. Lecture Videos
• 2. How to use Colaboratory.
  • 2.1. To start using
  • 2.2. Executing Shell commands in Coraboratory
  • 2.3. Executing Shell commands in Coraboratory
  • 2.4. Use your own Google Drive.
• 3. Introduction to Python
  • 3.1. Overview
  • 3.2. Python Basics
  • 3.3. Control statements
  • 3.4. Classes
• 4. Introduction to NumPy
  • 4.1. Overview
  • 4.2. Generate NumPy array
  • 4.3. Calculating NumPy arrays
  • 4.4. Statistic
  • 4.5. Matplotlib
• 5. Introduction to deep learning
  • 5.1. Flow of regression analysis by deep learning
  • 5.2. Data acquisition and preprocessing
  • 5.3. Training Neural Networks with TensorFlow-Keras
• 6. Introduction to PyTorch
  • 6.1. Automatic differentiation
  • 6.2. How to use the Datase and Dataloader
  • 6.3. Model building and training
  • 6.4. Prediction on test data
• 7. Transfer learning of Faster RCNN object recognition model using TorchVision
  • 7.1. Preparing a dataset
  • 7.2. Loading and configuring a Faster R-CNN model
  • 7.3. Prediction on a test image
  • 7.4. Application to Video

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