딥러닝 기반의 순방향 전파형 가중치 양자화 기법
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저자
주우정
강상길
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제어번호
106060897
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학술지명
정보기술아키텍처연구
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권호사항
Vol.
15
No.
2
[
2018
]
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발행처
한국엔터프라이즈아키텍처학회
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자료유형
학술저널
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수록면
245-252
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언어
Korean
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출판년도
2018
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등재정보
KCI등재
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판매처
'
딥러닝 기반의 순방향 전파형 가중치 양자화 기법' 의 참고문헌
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Trained ternary quantization
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The problem of overfitting
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TensorQuant: A Simulation Toolbox for Deep Neural Network Quantization
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Pruning convolutional neural networks for resource efficient transfer learning
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Phoneme probability estimation with dynamic sparsely connected artificial neural networks
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Parallel sparse matrix-vector and matrix-transpose-vector multiplication using compressed sparse blocks
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Neuronal mechanisms of developmental plasticity in the cat's visual system
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Learning multiple layers of features from tiny images
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Learning both weights and connections for efficient neural network
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Imagenet classification with deep conVol.utional neural networks
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Deepx: A software accelerator for low-power deep learning inference on mobile devices
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Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding
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Compressing deep convolutional networks using vector quantization
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Comparing biases for minimal network construction with back-propagation
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An efficient k-means clustering algorithm
'
딥러닝 기반의 순방향 전파형 가중치 양자화 기법'
의 유사주제(
) 논문