( en | de | ru )

 

Disambiguation of "Lee, Jinmook"

Author of the publication

copydeleteadd this publication to your clipboard
An Energy-Efficient and Scalable Deep Learning/Inference Processor With Tetra-Parallel MIMD Architecture for Big Data Applications.

, , , , , , and . IEEE Trans. Biomed. Circuits Syst., 9 (6): 838-848 (2015)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Jinmook Kim

Xavier Lee Lee

Bongsoo Lee

The role of negative regulators in coordination of the Myxococcus xanthus developmental program. Uni Marburg, (2009)

Min-Hi Lee

Induction and regulation of antiviral defence mechanisms through intracytoplasmic sensors. HU Berlin, (2009)

Kishik Lee

 

Other publications of authors with the same name

An energy-efficient deep learning processor with heterogeneous multi-core architecture for convolutional neural networks and recurrent neural networks., , , , and . COOL Chips, page 1-2. IEEE Computer Society, (2017)A 141.4 mW Low-Power Online Deep Neural Network Training Processor for Real-time Object Tracking in Mobile Devices., , , , and . ISCAS, page 1-5. IEEE, (2018)A Low-Power Deep Neural Network Online Learning Processor for Real-Time Object Tracking Application., , , and . IEEE Trans. Circuits Syst. I Regul. Pap., 66-I (5): 1794-1804 (2019)An Energy-Efficient Speech-Extraction Processor for Robust User Speech Recognition in Mobile Head-Mounted Display Systems., , , and . IEEE Trans. Circuits Syst. II Express Briefs, 64-II (4): 457-461 (2017)A 3.13nJ/sample energy-efficient speech extraction processor for robust speech recognition in mobile head-mounted display systems., , , and . ISCAS, page 1790-1793. IEEE, (2015)A 0.53mW ultra-low-power 3D face frontalization processor for face recognition with human-level accuracy in wearable devices., , , , and . ISCAS, page 1-4. IEEE, (2017)A 21mW low-power recurrent neural network accelerator with quantization tables for embedded deep learning applications., , and . A-SSCC, page 237-240. IEEE, (2017)14.2 DNPU: An 8.1TOPS/W reconfigurable CNN-RNN processor for general-purpose deep neural networks., , , and . ISSCC, page 240-241. IEEE, (2017)Low-Power Scalable 3-D Face Frontalization Processor for CNN-Based Face Recognition in Mobile Devices., , , , , and . IEEE J. Emerg. Sel. Topics Circuits Syst., 8 (4): 873-883 (2018)4.6 A1.93TOPS/W scalable deep learning/inference processor with tetra-parallel MIMD architecture for big-data applications., , , , , and . ISSCC, page 1-3. IEEE, (2015)