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89
S. Ju and S. Lee, "FPGA Implementation of Accurate and Low-Cost Keyword Spotting," in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2026, pp. 18762-18766.
S. Ju and S. Lee, "FPGA Implementation of Accurate and Low-Cost Keyword Spotting," in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, 2026, pp. 18762-18766.
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88
S. Ju and S. Lee, "Memory-Efficient Keyword Spotting," in Proc. Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 2025, pp. 341-345.
S. Ju and S. Lee, "Memory-Efficient Keyword Spotting," in Proc. Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 2025, pp. 341-345.
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87
H. Chae and S.Lee, "Small-footprint Convolutional Neural Network with Reduced Feature map for Voice Activity Detection," in Proc. of International Conference on Acoustics, Speech, and Signal Processin
H. Chae and S.Lee, "Small-footprint Convolutional Neural Network with Reduced Feature map for Voice Activity Detection," in Proc. of International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Apr., 2024.
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86
J. Park and S.Lee, "Energy-Efficient Image Processing Using Binary Neural Networks with Hadamard Transform", in Proceedings of the Asian Conference on Computer Vision (ACCV), Dec. 2022.
J. Park and S.Lee, "Energy-Efficient Image Processing Using Binary Neural Networks with Hadamard Transform", in Proceedings of the Asian Conference on Computer Vision (ACCV), Dec. 2022.
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85
M. Ha and S. Lee, "DMC: Differentiable Model Compression for Hardware-Efficient Convolutional Neural Network," in Proceedings of Design Automation Conference (DAC), San Francisco, CA, July 19-23, 2020
M. Ha and S. Lee, "DMC: Differentiable Model Compression for Hardware-Efficient Convolutional Neural Network," in Proceedings of Design Automation Conference (DAC), San Francisco, CA, July 19-23, 2020.
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84
M. Ha, S. Hwang, J. Kim, Y. Lee, and S. Lee, "Hierarchical Approximate Memory for Deep Neural Network Applications," Asilomar Conference on Signals, Systems, and Computers (ACSSC), Nov. 2020.
M. Ha, S. Hwang, J. Kim, Y. Lee, and S. Lee, "Hierarchical Approximate Memory for Deep Neural Network Applications," Asilomar Conference on Signals, Systems, and Computers (ACSSC), Nov. 2020.
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83
M. Ha, Y. Hyeon, Y. Lee, and S. Lee, "Selective deep convolutional neural network for low cost distorted image classification," Work-In-Progress Poster Session paper, Design Automation Conference (DAC
M. Ha, Y. Hyeon, Y. Lee, and S. Lee, "Selective deep convolutional neural network for low cost distorted image classification," Work-In-Progress Poster Session paper, Design Automation Conference (DAC), Las Vegas, NV, June 2019.
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82
S. Moon, H. Lee, Y. Byun, J. Park, J. Joe, S. Hwang, S. Lee, and Y. Lee, "FPGA-based sparsity-aware CNN accelerator for noise-resilient edge-level image recognition," IEEE Asian Solid-State Circuits C
S. Moon, H. Lee, Y. Byun, J. Park, J. Joe, S. Hwang, S. Lee, and Y. Lee, "FPGA-based sparsity-aware CNN accelerator for noise-resilient edge-level image recognition," IEEE Asian Solid-State Circuits Conference (A-SSCC), 2019.
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81
H. Kim, J. Lim, W. Hong, J. Park, Y.-S. Kim, M. Kim, and Y. Lee, "Design of a low-power BLE5-based wearable device for tracking movements of football players," IEEE International SoC Design Conference
H. Kim, J. Lim, W. Hong, J. Park, Y.-S. Kim, M. Kim, and Y. Lee, "Design of a low-power BLE5-based wearable device for tracking movements of football players," IEEE International SoC Design Conference (ISOCC), 2019. (Synopsys Award)
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80
J. Joe, J. Kung, S. Lee, and Y. Lee, "Similarity-based LSTM architecture for energy-efficient edge-level speech recognition," ACM/IEEE International Symposium on Low Power Electronics and Design (ISLP
J. Joe, J. Kung, S. Lee, and Y. Lee, "Similarity-based LSTM architecture for energy-efficient edge-level speech recognition," ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED), 2019.