Fellowship - Autonomous behavior acquisition based on media understanding
Japan

Job Reference: 000057

Location: Japan

Closing Date: 31/12/2018

Job Posted Date: 27/09/2018

Salary: C10M JPY

Employment Type: Toshiba Fellowship

Business Type: Research & Development

The use of AI-related technologies are widely expected to lead an evolutional change in  value creation and to counter the lack of human workforce in manufacturing, logistics, services and many other commercial fields. In the past, technologies such as autonomous driving based on image recognition and dialogue interface using speech recognition have been actively studied, but going forward, AI technology, which integrates a variety of information and enables autonomous judgment and action, will be required.
The successful candidate will focus on either

  1. Research and development of recognition and understanding of various media such as image, voice and text
  2. Research and development of agents such as next generation autonomous vehicles, robots and drones using automated decision-making and action based on the various information gathered
  3. Research and development of integration of the above to develop a new architecture to make more intelligent decision-making based on accumulated knowledge that can realize a high degree of autonomous activity

Toshiba has many experienced researchers who have a long-standing history of image and speech recognition research, and has many business areas including social infrastructure, electronic devices, and digital solutions  in which to apply the technologies developed.

Knowledge and Skills Required

Candidates are required to have a deep knowledge of at least one of the following fields: pattern recognition, speech recognition, machine learning, knowledge modeling, deep learning, reinforcement learning, and robotics. They should also have software implementation skills such as C, C++, C#, MATLAB(R) and/or python(TM) for building algorithms and conducting experiments.

Related Papers

[1] BiSeg: Simultaneous Instance Segmentation and Semantic Segmentation with Fully Convolutional Networks, Viet-Quoc Pham, Satoshi Ito, Tatsuo Kozakaya, BMVC, 2017
[2] COUNT Forest: CO-Voting Uncertain Number of Targets Using Random Forest for Crowd Density Estimation, Viet-Quoc Pham, Tatsuo Kozakaya, Osamu Yamaguchi, Ryuzo Okada, ICCV, 2015
[3] Random ensemble metrics for object recognition.  Tatsuo Kozakaya, Satoshi Ito, Susumu Kubota, ICCV, 2011
[4] Cat face detection with two heterogeneous features. Tatsuo Kozakaya, Satoshi Ito, Susumu Kubota, Osamu Yamaguchi, ICIP, 2009
[5] Fully automatic feature localization for medical images using a global vector concentration approach, Tatsuo Kozakaya, Tomoyuki Shibata, Tomoyuki Takeguchi, Masahide Nishiura, CVPR, 2008

 

This position is now closed. We are no longer accepting applications for this position.

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