Zobrazeno 1 - 10
of 125
pro vyhledávání: '"Liu, Juzheng"'
Publikováno v:
In Separation and Purification Technology 6 September 2024 343
Autor:
Su, Shiyu, Zhang, Qiaochu, Liu, Juzheng, Hassanpourghadi, Mohsen, Rasul, Rezwan, Chen, Mike Shuo-Wei
A digital finite impulse response (FIR) filter design is fully synthesizable, thanks to the mature CAD support of digital circuitry. On the contrary, analog mixed-signal (AMS) filter design is mostly a manual process, including architecture selection
Externí odkaz:
http://arxiv.org/abs/2112.07825
Autor:
Su, Shiyu, Zhang, Qiaochu, Hassanpourghadi, Mohsen, Liu, Juzheng, Rasul, Rezwan A, Chen, Mike Shuo-Wei
Analog mixed-signal (AMS) circuit architecture has evolved towards more digital friendly due to technology scaling and demand for higher flexibility/reconfigurability. Meanwhile, the design complexity and cost of AMS circuits has substantially increa
Externí odkaz:
http://arxiv.org/abs/2112.07824
Publikováno v:
In Solar Energy February 2024 269
Publikováno v:
In Separation and Purification Technology 19 February 2025 354 Part 2
Akademický článek
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Privacy recently emerges as a severe concern in deep learning, that is, sensitive data must be prohibited from being shared with the third party during deep neural network development. In this paper, we propose Morphed Learning (MoLe), an efficient a
Externí odkaz:
http://arxiv.org/abs/1909.07632
Autor:
Alyamkin, Sergei, Ardi, Matthew, Berg, Alexander C., Brighton, Achille, Chen, Bo, Chen, Yiran, Cheng, Hsin-Pai, Fan, Zichen, Feng, Chen, Fu, Bo, Gauen, Kent, Goel, Abhinav, Goncharenko, Alexander, Guo, Xuyang, Ha, Soonhoi, Howard, Andrew, Hu, Xiao, Huang, Yuanjun, Kang, Donghyun, Kim, Jaeyoun, Ko, Jong Gook, Kondratyev, Alexander, Lee, Junhyeok, Lee, Seungjae, Lee, Suwoong, Li, Zichao, Liang, Zhiyu, Liu, Juzheng, Liu, Xin, Lu, Yang, Lu, Yung-Hsiang, Malik, Deeptanshu, Nguyen, Hong Hanh, Park, Eunbyung, Repin, Denis, Shen, Liang, Sheng, Tao, Sun, Fei, Svitov, David, Thiruvathukal, George K., Zhang, Baiwu, Zhang, Jingchi, Zhang, Xiaopeng, Zhuo, Shaojie
Computer vision has achieved impressive progress in recent years. Meanwhile, mobile phones have become the primary computing platforms for millions of people. In addition to mobile phones, many autonomous systems rely on visual data for making decisi
Externí odkaz:
http://arxiv.org/abs/1904.07714
Autor:
Alyamkin, Sergei, Ardi, Matthew, Brighton, Achille, Berg, Alexander C., Chen, Yiran, Cheng, Hsin-Pai, Chen, Bo, Fan, Zichen, Feng, Chen, Fu, Bo, Gauen, Kent, Go, Jongkook, Goncharenko, Alexander, Guo, Xuyang, Nguyen, Hong Hanh, Howard, Andrew, Huang, Yuanjun, Kang, Donghyun, Kim, Jaeyoun, Kondratyev, Alexander, Lee, Seungjae, Lee, Suwoong, Lee, Junhyeok, Liang, Zhiyu, Liu, Xin, Liu, Juzheng, Li, Zichao, Lu, Yang, Lu, Yung-Hsiang, Malik, Deeptanshu, Park, Eunbyung, Repin, Denis, Sheng, Tao, Shen, Liang, Sun, Fei, Svitov, David, Thiruvathukal, George K., Zhang, Baiwu, Zhang, Jingchi, Zhang, Xiaopeng, Zhuo, Shaojie
The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcomputing.ieee.org/lpirc) is an annual competition started in 2015. The competition identifies the best technologies that can classify and detect objects in images efficiently (short
Externí odkaz:
http://arxiv.org/abs/1810.01732
Privacy recently emerges as a severe concern in deep learning, that is, sensitive data must be prohibited from being shared with the third party during deep neural network development. In this paper, we propose Morphed Learning (MoLe), an efficient a
Externí odkaz:
http://arxiv.org/abs/1809.09968