机构

• 自动化研究所 [2]
• 长春光学精密机械与物... [1]
• 西安光学精密机械研究... [1]

采集方式

• OAI收割 [4]

内容类型

• 会议论文 [2]
• 期刊论文 [2]

发表日期

• 2021 [1]
• 2019 [1]
• 2014 [1]
• 2010 [1]

学科主题

筛选

浏览/检索结果: 共4条，第1-4条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择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作者升序作者降序 Audio-Visual Speech Separation with Visual Features Enhanced by Adversarial Training 会议论文  OAI收割 线上会议, 2021-7-18 作者:  Zhang Peng;  Xu Jiaming;  Shi Jing;  Hao Yunzhe;  Qin Lei   |  收藏  |  浏览/下载：38/0  |  提交时间：2021/06/21 audio-visual speech separation  robust  adversarial training method  time-domain approach   Robust Space-Frequency Joint Representation for Remote Sensing Image Scene Classification 期刊论文  OAI收割 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2019, 卷号: 57, 期号: 10, 页码: 7492-7502 作者:  Fang, Jie;  Yuan, Yuan;  Lu, Xiaoqiang;  Feng, Yachuang   |  收藏  |  浏览/下载：63/0  |  提交时间：2019/11/01 Frequency domain  joint representation  remote sensing image classification  robust  space domain   Learning Convolutional Domain-Robust Representations for Cross-View Face Recognition 期刊论文  OAI收割 IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2014, 卷号: E97D, 期号: 12, 页码: 3239-3243 作者:  Chen, Xue;  Wang, Chunheng;  Xiao, Baihua;  Gao, Song 收藏  |  浏览/下载：117/0  |  提交时间：2015/08/12 cross-view  face recognition  convolutional deep belief networks  domain-robust   Speech signal enhancement through wavelet domain MMSE filtering (EI CONFERENCE) 会议论文  OAI收割 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China Fenghua Z.; Le Y.; Jian W.; Qiang S. 收藏  |  浏览/下载：30/0  |  提交时间：2013/03/25 A new speech enhancement system that combine robust signal enhancement and minimum signal distortion is proposed in this paper. The proposed method introduces frequency depended  parametric  MMSE filtering techniques that involve wavelet packets. Voice activity detection (VAD) is used to further distinguish speech from noise and help to adaptively remove noise components from color noise eruptive noisy speech  while perceptual criteria is also taken into account. Experimental results and objective quality measurement test results validate the proposed speech enhancement system and illustrate the benefit of the proposed wavelet domain MMSE filtering as an excellent speech enhancement method to provide sufficient noise reduction and good intelligibility and perceptual quality  without causing considerable signal distortion and musical background noise method. 2010 IEEE.