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TechInnovation @SG 2016

September 20-21, 2016 | Event

Panasonic R&D Center Singapore partook in TechInnovation 2016 as one of the exhibitors to appeal to local collaboration through crowd-sourcing and crowd-pitching. TechInnovation has been a technology-industry brokerage event organized by IPI Singapore since 2012. It serves as a platform to bring together international and Singapore technology providers and seekers to explore technology and business collaboration opportunities through open innovation, and this year it successfully attracted over 2,700 participants from about 40 nations. At this, PIPM (Panasonic Intellectual Property Management Co., Ltd.), as Panasonic R&D Center Singapore’s co-exhibitor, hit a great success in attracting many enquiries and interests in their technology offer through licensing, while IPG of Panasonic R&D Center Singapore gained extensive exposure and further established a presence in the local technology market.

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Panasonic R&D Center Singapore Received the ISCIT 2018 Best Paper Award

Teaming up with King Mongkut’s University of Technology Thonburi (KMUTT) to co-author a paper titled “Image Denoising with Deep Convolutional and Multi-directional LSTM Networks under Poisson Noise Environments”, Panasonic R&D Center Singapore (PRDCSG) received the Best Paper Award at ISCIT 2018 held in Bangkok on 26-29 September 2018.

ISDN Holdings’ NovaPeak partners with Panasonic HD to Scale LiveInspect.AI globally

LiveInspect.AI Development Team lead by Dr. Takeshi Ando Managing Director of Panasonic R&D Center Singapore (front right) and Mr. Eugene…

Panasonic’s Flagship LZ2000 OLED TV Continually Powered by Panasonic R&D Center Singapore’s Neural Network Architecture

At this year’s Consumer Electronics Show (CES) held on 4th -7th January, Panasonic unveiled its new flagship OLED TV for…

Joint collaborations with I2R: achieved the No. 2 position at MEC 2017 plus a paper accepted at ICMI 2017

In collaboration with the Institute for Infocomm Research (I2R), Panasonic R&D Center Singapore achieved the No. 2 position in the audio-visual emotion recognition sub-challenge of the Multimodal Emotion Recognition Challenge (MEC) 2017. The challenge (*1) is aimed at the comparison of multimedia processing and machine learning methods for automatic audio and visual emotion analysis.