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A 141.4 mW Low-Power Online Deep Neural Network Training Processor for Real-time Object Tracking in Mobile Devices.

D. Han, J. Lee, J. Lee, S. Choi, и H. Yoo. ISCAS, стр. 1-5. IEEE, (2018)

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Muxin Han

Luyang Han

Mei Han

Johannes Han

Bing Han

Другие публикации лиц с тем же именем

A 141.4 mW Low-Power Online Deep Neural Network Training Processor for Real-time Object Tracking in Mobile Devices.D. Han, J. Lee, J. Lee, S. Choi, и H. Yoo. ISCAS, стр. 1-5. IEEE, (2018)A Mobile 3-D Object Recognition Processor With Deep-Learning-Based Monocular Depth Estimation.D. Im, G. Park, Z. Li, J. Ryu, S. Kang, D. Han, J. Lee, W. Park, H. Kwon, и H. Yoo. IEEE Micro, 43 (3): 74-82 (мая 2023)An Overview of Sparsity Exploitation in CNNs for On-Device Intelligence With Software-Hardware Cross-Layer Optimizations.S. Kang, G. Park, S. Kim, S. Kim, D. Han, и H. Yoo. IEEE J. Emerg. Sel. Topics Circuits Syst., 11 (4): 634-648 (2021)DT-CNN: Dilated and Transposed Convolution Neural Network Accelerator for Real-Time Image Segmentation on Mobile Devices.D. Im, D. Han, S. Choi, S. Kang, и H. Yoo. ISCAS, стр. 1-5. IEEE, (2019)NeRPIM: A 4.2 mJ/frame Neural Rendering Processing-in-memory Processor with Space Encoding Block-wise Mapping for Mobile Devices.W. Jo, S. Kim, J. Lee, D. Han, S. Kim, S. Choi, и H. Yoo. VLSI Technology and Circuits, стр. 1-2. IEEE, (2023)A Low-power and Real-time 3D Object Recognition Processor with Dense RGB-D Data Acquisition in Mobile Platforms.D. Im, G. Park, J. Ryu, Z. Li, S. Kang, D. Han, J. Lee, W. Park, H. Kwon, и H. Yoo. COOL CHIPS, стр. 1-3. IEEE, (2022)20.8 Space-Mate: A 303.5mW Real-Time Sparse Mixture-of-Experts-Based NeRF-SLAM Processor for Mobile Spatial Computing.G. Park, S. Song, H. Sang, D. Im, D. Han, S. Kim, H. Lee, и H. Yoo. ISSCC, стр. 374-376. IEEE, (2024)A Low-power and Real-time Neural-Rendering Dense SLAM Processor with 3-Level Hierarchical Sparsity Exploitation.G. Park, S. Song, H. Sang, D. Im, D. Han, S. Kim, H. Lee, и H. Yoo. COOL CHIPS, стр. 1-3. IEEE, (2024)LNPU: A 25.3TFLOPS/W Sparse Deep-Neural-Network Learning Processor with Fine-Grained Mixed Precision of FP8-FP16.J. Lee, J. Lee, D. Han, J. Lee, G. Park, и H. Yoo. ISSCC, стр. 142-144. IEEE, (2019)HNPU: An Adaptive DNN Training Processor Utilizing Stochastic Dynamic Fixed-Point and Active Bit-Precision Searching.D. Han, D. Im, G. Park, Y. Kim, S. Song, J. Lee, и H. Yoo. IEEE J. Solid State Circuits, 56 (9): 2858-2869 (2021)

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