Preferred Networks is a Japanese AI startup founded in 2014 that develops deep learning technologies. They presented at CEATEC JAPAN 2018 on their research using convolutional neural networks for computer vision tasks like object detection. They discussed techniques like residual learning and how they have achieved state-of-the-art results on datasets like COCO by training networks on large amounts of data using hundreds of GPUs.

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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)
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He. et.al, Deep Residual Learning for
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T. Akiba, et.al. PFDet: 2nd Place Solution to Open Images Challenge 2018 Object Detection Track. ECCV2018.

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K. Takahashi, J. Tan. Deep Visuo-Tactile Learning: Estimation of Tactile Properties from Images. ICRA2019.

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J. Hatori, et.al. Interactively Picking Real-World Objects with Unconstrained Spoken Language Instructions. ICRA2018.

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Photo by Kuha455405 / CC BY-SA 3.0

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