Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Huizi Mao"'
Publikováno v:
Molecular Medicine, Vol 30, Iss 1, Pp 1-14 (2024)
Abstract Background Programmed cell death is an important mechanism for the development of hepatic ischemia and reperfusion (IR) injury, and multiple novel forms of programmed cell death are involved in the pathological process of hepatic IR. ERRFI1
Externí odkaz:
https://doaj.org/article/4511074bd11c4c1892009c23b54c4e9f
Publikováno v:
IEEE Transactions on Emerging Topics in Computing. 6:417-431
Convolutional neural network (CNN) based methods have achieved great success in image classification and object detection tasks. However, unlike the image classification task, object detection is much more computation-intensive and energy-consuming s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::22a235441265fdfb67df22a6865b6925
https://doi.org/10.1109/tetc.2016.2593643
https://doi.org/10.1109/tetc.2016.2593643
Publikováno v:
ICCV
Average precision (AP) is a widely used metric to evaluate detection accuracy of image and video object detectors. In this paper, we analyze object detection from videos and point out that AP alone is not sufficient to capture the temporal nature of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f36ab32cb3e5805fe7ff18d41124c73c
https://doi.org/10.1109/iccv.2019.00066
https://doi.org/10.1109/iccv.2019.00066
Autor:
Huazhong Yang, Jincheng Yu, Yu Wang, Kaiyuan Guo, Xuefei Ning, Huizi Mao, Tianqi Tang, Yiming Hu, Boxun Li, Jiantao Qiu, Song Yao
Publikováno v:
DATE
In recent years, Convolutional Neural Network (CNN) has been widely applied in computer vision tasks and has achieved significant improvement in image object detection. The CNN methods consume more computation as well as storage, so GPU is introduced
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce36fb8350b96c7d0ca7585696666b96
https://doi.org/10.23919/date.2018.8342100
https://doi.org/10.23919/date.2018.8342100
Publikováno v:
CVPR Workshops
Sparsity helps reducing the computation complexity of DNNs by skipping the multiplication with zeros. The granularity of sparsity affects the efficiency of hardware architecture and the prediction accuracy. In this paper we quantitatively measure the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b17f26cf5529598987270ef7346e51cf
https://doi.org/10.1109/cvprw.2017.241
https://doi.org/10.1109/cvprw.2017.241
Publikováno v:
Hot Chips Symposium
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53ae43b5842ee0d0bbed988b65e382ca
https://doi.org/10.1109/hotchips.2016.7936226
https://doi.org/10.1109/hotchips.2016.7936226
Autor:
Yu Wang, Huazhong Yang, Dongliang Xie, Junlong Kang, Yubin Li, Song Han, Song Yao, Hong Luo, Huizi Mao, William J. Dally, Xin Li, Yiming Hu
Publikováno v:
FPGA
Long Short-Term Memory (LSTM) is widely used in speech recognition. In order to achieve higher prediction accuracy, machine learning scientists have built larger and larger models. Such large model is both computation intensive and memory intensive.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91776ff82aff68bd9dfb97a65e805a78
Publikováno v:
ISCA
State-of-the-art deep neural networks (DNNs) have hundreds of millions of connections and are both computationally and memory intensive, making them difficult to deploy on embedded systems with limited hardware resources and power budgets. While cust
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d1bd52636e4d7f7731e56c609334cda
Autor:
Yung-Hsiang Lu, Alan M. Kadin, Alexander C. Berg, Thomas M. Conte, Erik P. DeBenedictis, Rachit Garg, Ganesh Gingade, Bichlien Hoang, Yongzhen Huang, Boxun Li, Jingyu Liu, Wei Liu, Huizi Mao, Junran Peng, Tianqi Tang, Elie K. Track, Jingqiu Wang, Tao Wang, Yu Wang, Jun Yao
Publikováno v:
2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38c0158a6e71bcc488c34f89aebe4cc2
https://doi.org/10.1109/iccad.2015.7372672
https://doi.org/10.1109/iccad.2015.7372672