深層学習で切り拓くパーソナルロボットの未来
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2019/06/28 東京大学駒場キャンパスで開催された、先端技術セミナー工学最前線での講演資料です
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深層学習で切り拓くパーソナルロボットの未来
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- 3. Preferred Networks (PFN) l 2014 3 l l l 3
- 4. 6 G CEATEC JAPAN 2018＠幕張メッセ 2018年10月16日
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- 8. CEATEC JAPAN 2018 (Oct 16–19, 2018) 8
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- 10. 10
- 11. 11
- 12. 12
- 13. 0 1 l l 2012 l He. et.al, Deep Residual Learning for Image Recognition. CVPR 2016.
- 14. 14
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- 38. l l 38 K. Takahashi, J. Tan. Deep Visuo-Tactile Learning: Estimation of Tactile Properties from Images. ICRA2019.
- 39. l l 39 J. Hatori, et.al. Interactively Picking Real-World Objects with Unconstrained Spoken Language Instructions. ICRA2018.
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