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检索条件"机构=Semiconductor Neural Network Intelligent Perception and Computing Technology"
61 条 记 录,以下是21-30 订阅
排序:
PGGAN: Improve Password Cover Rate Using the Controller
PGGAN: Improve Password Cover Rate Using the Controller
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2021 International Conference on Computer network Security and Software Engineering, CNSSE 2021
作者: Guo, Xiaozhou Liu, Yi Tan, Kaijun Jin, Min Lu, Huaxiang Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China University of Chinese Academy of Sciences Beijing100089 China Cas Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Beijing200031 China Semiconductor Neural Network Intelligent Perception and Computing Technology Beijing Key Lab Beijing100083 China
Password generation model based on generative adversarial network usually has the problem of high duplicate rate, which further leads to low cover rate. In this regard, we propose PGGAN model. It sets up an additional... 详细信息
来源: 评论
Sdgan: Improve Speech Enhancement Quality by Information Filter  6
Sdgan: Improve Speech Enhancement Quality by Information Fil...
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2021 6th International Symposium on Advances in Electrical, Electronics and Computer Engineering, ISAEECE 2021
作者: Guo, Xiaozhou Liu, Yi Mao, Wenyu Li, Jixing Li, Wenchang Gong, Guoliang Lu, Huaxiang Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China University of Chinese Academy of Sciences Beijing100089 China CAS Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Beijing200031 China Semiconductor Neural Network Intelligent Perception and Computing Technology Beijing Key Lab Beijing100083 China
The speech denoising model based on adversarial generative network has achieved better results than the traditional machine learning model. In this paper, for the short cut connection in the generator, we discuss its ... 详细信息
来源: 评论
A neural-guided dynamic symbolic network for exploring mathematical expressions from data  24
A neural-guided dynamic symbolic network for exploring mathe...
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Proceedings of the 41st International Conference on Machine Learning
作者: Wenqiang Li Weijun Li Lina Yu Min Wu Linjun Sun Jingyi Liu Yanjie Li Shu Wei Yusong Deng Meilan Hao AnnLab Institute of Semiconductors Chinese Academy of Sciences Beijing China and School of Electronic Electrical and Communication Engineering & School of Integrated Circuits University of Chinese Academy of Sciences Beijing China and Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology Beijing China AnnLab Institute of Semiconductors Chinese Academy of Sciences Beijing China and School of Electronic Electrical and Communication Engineering & School of Integrated Circuits and Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology Beijing China and Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing China
Symbolic regression (SR) is a powerful technique for discovering the underlying mathematical expressions from observed data. Inspired by the success of deep learning, recent deep generative SR methods have shown promi...
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Research on Convolution Decomposition and Hardware Acceleration based on FPGA
Research on Convolution Decomposition and Hardware Accelerat...
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International Conference on Computer Engineering and Applications (ICCEA)
作者: Jinzhong He Weijun Li Jian Xu Ming Zhang Huiqu Yang Institute of Semiconductors Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology Beijing China DapuStor Corporation Shenzhen China
Convolutional neural network (CNN) is an artificial intelligence algorithm with a wide application foundation. In recent years, to improve the computational speed of the computation-intensive CNN models, many research...
来源: 评论
Point convolutional neural network algorithm for Ising model ground state research based on spring vibration
arXiv
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arXiv 2023年
作者: Jiang, Zhelong Chen, Gang Qiao, Ruixiu Feng, Pengcheng Chen, Yihao Su, Junjia Zhao, Zhiyuan Jin, Min Chen, Xu Li, Zhigang Lu, Huaxiang Institute of Semiconductors Chinese Academy of Sciences Beijing China Materials and Optoelectronics Research Center University of Chinese Academy of Sciences Beijing China School of Microelectronics University of Science and Technology of China Hefei China College of Microelectronics University of Chinese Academy of Sciences Beijing China Semiconductor Neural Network Intelligent Perception and Computing Technology Beijing Key Laboratory Beijing China
The ground state search of the Ising model can be used to solve many combinatorial optimization problems. Under the current computer architecture, an Ising ground state search algorithm suitable for hardware computing... 详细信息
来源: 评论
Fitting objects with implicit polynomials by deep neural network
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Optoelectronics Letters 2023年 第1期19卷 60-64页
作者: LIU Jingyi YU Lina SUN Linjun TONG Yuerong WU Min LI Weijun Institute of Semiconductors Chinese Academy of SciencesBeijing100083China Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology Beijing100083China School of Integrated Circuits University of Chinese Academy of SciencesBeijing100049China Shenzhen DAPU Microelectronics Co. Ltd.Shenzhen518116China
Implicit polynomials(IPs)are considered as a powerful tool for object curve fitting tasks due to their simplicity and fewer *** traditional linear methods,such as 3L,Min Var,and Min Max,often achieve good performances... 详细信息
来源: 评论
Deep Learning-based 3D Point Cloud Classification: A Systematic Survey and Outlook
arXiv
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arXiv 2023年
作者: Zhang, Huang Wang, Changshuo Tian, Shengwei Lu, Baoli Zhang, Liping Ning, Xin Bai, Xiao The School of Software Xinjiang University Xinjiang830000 China The Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China Center of Materials Science and Optoelectronics Engineering School of Microelectronics Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology Beijing100083 China University of Chinese Academy of Sciences Beijing100049 China Cognitive Computing Technology Joint Laboratory Wave Group Beijing102208 China Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology Beijing100083 China The School of Computer Science and Engineering Beihang University Beijing100083 China
In recent years, point cloud representation has become one of the research hotspots in the field of computer vision, and has been widely used in many fields, such as autonomous driving, virtual reality, robotics, etc.... 详细信息
来源: 评论
SSCGAN: Speech style conversion based on GAN
SSCGAN: Speech style conversion based on GAN
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2022 International Conference on Algorithms, Microchips and network Applications
作者: Li, Jixing Guo, Xiaozhou Shen, Ronxuan Lu, Huaxiang Wang, Xinggang Cao, Zhanzhong Zhang, Chi Mao, Wenyu Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China University of Chinese Academy of Sciences Beijing100089 China Materials and Optoelectronics Research Center University of Chinese Academy of Sciences Beijing100083 China College of Microelectronics University of Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China Semiconductor Neural Network Intelligent Perception and Computing Technology Beijing Key Laboratory Beijing100083 China Nanjing Research Institute of Information Technology Nanjing210009 China
Speech conversion has significant applications in medical, robotics, and other industries. With the rise of deep learning, CycleGAN is widely used in speech conversion technology. However, the existing CycleGAN-based ... 详细信息
来源: 评论
PruneSymNet: A Symbolic neural network and Pruning Algorithm for Symbolic Regression
arXiv
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arXiv 2024年
作者: Wu, Min Li, Weijun Yu, Lina Li, Wenqiang Liu, Jingyi Li, Yanjie Hao, Meilan AnnLab Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China Center of Materials Science and Optoelectronics Engineering School of Microelectronics University of Chinese Academy of Sciences Beijing100049 China Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology Beijing100083 China
Symbolic regression aims to derive interpretable symbolic expressions from data in order to better understand and interpret data. In this study, a symbolic network called PruneSymNet is proposed for symbolic regressio... 详细信息
来源: 评论
Incorporating Higher-Knowledge into Deep Symbolic Regression Under Generative neural network Framework
SSRN
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SSRN 2024年
作者: Liu, Jingyi Li, Weijun Yu, Lina Wu, Min Li, Wenqiang Li, Yanjie Hao, Meilan Annlab Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China Center of Materials Science and Optoelectronics Engineering School of Integrated Circuits University of Chinese Academy of Sciences Beijing100049 China Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology Beijing100083 China
This paper introduces MSR, a generative neural network-based framework that incorporates an automatic module learning feature, aiming to enhance the search accuracy of Symbolic Regression (SR). Unlike existing deep mo... 详细信息
来源: 评论