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        Artificial Intelligence Computing Research Laboratory

        Artificial Intelligence Computing Research Laboratory is researching and developing core technologies to fulfill its pivotal role in ETRI’s vision of ‘Technology pioneer creating a happy future world through digital innovation.’

        We are promoting the development of ultra-high performance hardware and software strategic technology for AI. We have established a strategic goal to realize disruptive innovative computing through the development of computing systems and infrastructure to overcome performance limitations. To achieve this goal, we are developing key technologies for future computing systems, including hardware using intelligent semiconductors and quantum computing, but also system software supports them.

        In particular, we pursue open technology innovation through close collaboration with domestic and foreign universities and companies so that the computing systems developed by ETRI based on AI supercomputer and cyber security technology can be applied to national infrastructure to solve social problems.

        Artificial Intelligence Research Laboratory Introduction Video
        Artificial Intelligence Computing Research Laboratory Titles
        Period: : 20250701 ~
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        논문 검색결과
        Type Year Title Cited Download
        Journal
        2025 BCRNet-SNN: Body Channel Response-Aware Spiking Neural Network for User Recognition   Kang Tae Wook   IEEE Transactions on Industrial Informatics, v.21, no.8, pp.6017-6027 0
        Journal
        2025 An Ultracompact 6-bit Phase Shifter Using Active Balun Embedded Vector-Sum Core   Park Seonjeong   IEEE Microwave and Wireless Technology Letters, v.35, no.7, pp.1025-1028
        Conference
        2025 An Efficient Hardware Architecture of Phase-locked coherence device in a distributed radar system suitable for disaster environments   Park Seong Mo   International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) 2025, pp.1057-1060
        Conference
        2025 Operator-Level Efficiency Evaluation of Lightweight Neural Networks: YOLOv8, MobileNetV2, and EfficientViT   Kim You Jin   한국컴퓨터 종합 학술대회 2025, pp.803-805
        Conference
        2025 Performance Evaluation of Ethernet-Based Remote Memory Expansion Subsystem   Kim Young Woo   International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) 2025, pp.403-406
        Journal
        2025 Quantum Implementation of S-Boxes Based on Polynomial Evaluation   Chung Do Young   Electronics Letters, v.61, no.1, pp.1-7