Hironobu Fujiyoshi

藤吉 弘亘
Professor, College of Engineering, Chubu University
Artificial Intelligence, Deep Learning, Computer Vision, Visual Explanation

Title of Presentation

“Visualizing Direction of Attention to Understand AI Decisions”

Artificial intelligence systems using deep learning have achieved image and speech recognition at performance levels on par with human beings. However, an issue is not being able to understand the basis on which a deep learning system determines its output. In this lecture, we introduce Attention Branch Network (ABN), which outputs attention, an area that deep learning focuses on when determining inferential results. ABN is a deep learning network that can contribute to improving recognition performance while acquiring the attention mechanism. As application examples of ABN, we introduce ABN’s visual explanation of automated driving and medical diagnosis decisions. Visualization of attention here means being able to view the AI’s direction of attention. This technology holds great promise as an approach for interpreting the basis for decisions output by an AI system.


Web Site URL
A brief Biography(As of April 1, 2019)
1997 Ph.D., Chubu University
1997 Postdoctoral Fellow, Robotics Institute, Carnegie Mellon University
2000 Senior Assistant Professor, Department of Computer Science, College of Engineering, Chubu University
2004 Associate Professor, Chubu University
2005 – 2006 Visiting Researcher, Robotics Institute, Carnegie Mellon University
2010 – Present Professor, Chubu University
2014 – Present Visiting Professor, Nagoya University
Details of selected Awards and Honors
A list of selected Publications