QQ客服 官方微博 反馈留言

浏览/检索结果: 共7条，第1-7条 帮助 限定条件 发表日期：2018     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 REAL-TIME DETECTION OF ANCIENT ARCHITECTURE FEATURES BASED ON SMARTPHONES 会议论文 PROCEEDINGS OF THE ASME CONFERENCE ON SMART MATERIALS, ADAPTIVE STRUCTURES AND INTELLIGENT SYSTEMS, 2017, VOL 2, 2018-01-01 作者:  Zou, Zheng;  Wang, Niannian;  Zhao, Peng;  Zhao, Xuefeng 收藏  |  浏览/下载：6/0  |  提交时间：2019/12/02 ancient architecture feature  smartphone  realtime object detection  deep learning  convolution neural network  SSD-Mobilenet   Relation Classification via LSTMs Based on Sequence and Tree Structure 期刊论文 IEEE ACCESS, 2018, 卷号: 6, 页码: 64927-64937 作者:  Dai, Yuanfei;  Guo, Wenzhong;  Chen, Xing;  Zhang, Zuwen 收藏  |  浏览/下载：4/0  |  提交时间：2019/11/21 tree structure LSTM  Relation classification  attention mechanism  two channels architecture  deep neural network   Deblurring retinal optical coherence tomography via a convolutional neural network with anisotropic and double convolution layer 期刊论文 IET COMPUTER VISION, 2018, 卷号: 12, 期号: 6, 页码: 900-907 作者:  Lian, Jian;  Hou, Sujuan;  Sui, Xiaodan;  Xu, Fangzhou;  Zheng, Yuanjie 收藏  |  浏览/下载：16/0  |  提交时间：2019/12/11 biomedical optical imaging  neural nets  eye  optical tomography  medical image processing  learning (artificial intelligence)  deconvolution  convolution  image restoration  retinal optical coherence  tomography  double convolution layer  image pre-processing tasks  optical coherence tomography systems  degradation effects  current  deblurring research  suitable degradation models  deconvolution  operators  model-based solutions  nonmodel architecture  deep  convolutional neural network  parameter-free situations  deep learning  strategy  traditional model  neural network architectures  retinal OCT  images  state-of-the-art model  OCT deblurring methods   Application of long short-term memory neural network for multi-step travel time forecasting on urban expressways 会议论文 CICTP 2017: Transportation Reform and Change - Equity, Inclusiveness, Sharing, and Innovation - Proceedings of the 17th COTA International Conference of Transportation Professionals 作者:  Zhang, Z.;  Wang, Y.;  Chen, P.;  Yu, G. 收藏  |  浏览/下载：3/0  |  提交时间：2019/12/30 Brain  Long short-term memory  Network architecture  Traffic control  Travel time  Non-parametric algorithm  Probe vehicle data  State of the art  Temporal evolution  Time series method  Traffic features  Travel time forecasting  Urban expressway  Deep learning   swCaffe: a Parallel Framework for Accelerating Deep Learning Applications on Sunway TaihuLight 会议论文 2018 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING (CLUSTER), 2018-01-01 作者:  Li, Liandeng;  Fang, Jiarui;  Fu, Haohuan;  Jiang, Jinlei;  Zhao, Wenlai 收藏  |  浏览/下载：10/0  |  提交时间：2019/12/30 Cluster computing  Deep neural networks  Network architecture  Network layers  Stochastic systems  Supercomputers  Heterogeneous many-core architectures  High efficient  Many-core architecture  Multiple processors  Optimization strategy  Parallel framework  Stochastic gradient descent  Synchronization scheme  Computer architecture   A convolutional neural network based classifier for uncompressed malware samples 会议论文 Proceedings of the ACM Conference on Computer and Communications Security 作者:  Yang, C.;  Wen, Y.;  Guo, J.;  Song, H.;  Li, L. 收藏  |  浏览/下载：5/0  |  提交时间：2019/12/30 Computer architecture  Computer crime  Convolution  Deep learning  Image classification  Network architecture  Neural networks  Complete information  Convolutional neural network  Design classifiers  Gray-scale images  Learning-based methods  Malware classifications  Malware detection  Malware families  Malware   A Computing Efficient Hardware Architecture for Sparse Deep Neural Network Computing 会议论文 2018 14th IEEE International Conference on Solid-State and Integrated Circuit Technology, ICSICT 2018 - Proceedings 作者:  Zhang, Y.;  Ouyang, P.;  Yin, S.;  Zhao, W.;  Wei, S. 收藏  |  浏览/下载：2/0  |  提交时间：2019/12/30 Integrated circuits  Memory architecture  Network architecture  Neural networks  Convolutional neural network  Dataflow  Hardware architecture  Load imbalance  Memory consumption  State of the art  State-of-the-art performance  Switching strategies  Deep neural networks