
Company News
Panasonic R&D Center Singapore’s Technology – LVNet for Photo Management – Incorporated into Panasonic’s New DIGA Models to Be Commercially Launched in Japan
October 01, 2020 | Project
New models of Panasonic’s Blu-ray recorder DIGA will be launched in Japan on 16th October 2020. (Model Name: DMR-4T401・4CT401 / DMR-4T301・4CT301 / DMR-4T201・4CT201). These 4K DIGA models contain new AI-based features of photo classification and photo slideshow. The AI capability is powered by Panasonic R&D Center Singapore’s proprietary neural network named Lightweight-and-Versatile Network (LVNet), which was co-developed with the Digital Transformation Development Center of AP company. When photos and videos are imported into these DIGA models, the AI will automatically generate albums organized by subjects and events such as people, animals and landscapes. The photos classified there will then be summarized as a one-minute video, providing viewers with a new way to enjoy photography.
https://panasonic.jp/diga/products/4t401_4t301_4t201.html
Related Posts
IP Week @ SG 2016
The Intellectual Property Group (IPG) of Panasonic R&D Center Singapore (PRDCSG) participated, as one of the exhibitors, in IP Ecosystem…
Read morePanasonic ranked #1 in Mugshot category of NIST FRVT 1:1 Challenge
PRDCSG once again kept Panasonic’s flag flying high in the global arena. In the latest Performance Summary of the NIST*…
Read morePanasonic R&D Center Singapore’s paper accepted for Publication in an Upcoming Issue of the Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Teaming up with Nanjing University of Science and Technology (NUST), Panasonic R&D Center Singapore co-authored a journal paper titled “Covariance…
Read moreJoint 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.
Read more