Zobrazeno 1 - 10
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pro vyhledávání: '"Yang, Yukuan"'
Huge computational costs brought by convolution and batch normalization (BN) have caused great challenges for the online training and corresponding applications of deep neural networks (DNNs), especially in resource-limited devices. Existing works on
Externí odkaz:
http://arxiv.org/abs/2105.13890
Semantic segmentation has been a major topic in research and industry in recent years. However, due to the computation complexity of pixel-wise prediction and backpropagation algorithm, semantic segmentation has been demanding in computation resource
Externí odkaz:
http://arxiv.org/abs/2011.14504
Few-shot learning has recently emerged as a new challenge in the deep learning field: unlike conventional methods that train the deep neural networks (DNNs) with a large number of labeled data, it asks for the generalization of DNNs on new classes wi
Externí odkaz:
http://arxiv.org/abs/2010.11714
Recently deep neural networks (DNNs) have been successfully introduced to the field of lensless imaging through scattering media. By solving an inverse problem in computational imaging, DNNs can overcome several shortcomings in the conventional lensl
Externí odkaz:
http://arxiv.org/abs/1912.12419
Autor:
Yang, Zheyu, Wu, Yujie, Wang, Guanrui, Yang, Yukuan, Li, Guoqi, Deng, Lei, Zhu, Jun, Shi, Luping
Computer-science-oriented artificial neural networks (ANNs) have achieved tremendous success in a variety of scenarios via powerful feature extraction and high-precision data operations. It is well known, however, that ANNs usually suffer from expens
Externí odkaz:
http://arxiv.org/abs/1909.12942
Deep neural network (DNN) quantization converting floating-point (FP) data in the network to integers (INT) is an effective way to shrink the model size for memory saving and simplify the operations for compute acceleration. Recently, researches on D
Externí odkaz:
http://arxiv.org/abs/1909.02384
Publikováno v:
In Neurocomputing 28 October 2022 511:175-186
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Publikováno v:
In Neurocomputing 24 September 2021 454:101-112
Publikováno v:
In Neural Networks September 2021 141:420-432