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浏览/检索结果: 共5条，第1-5条 帮助 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 Deep Learning Based Retrieval of Forest Aboveground Biomass from Combined LiDAR and Landsat 8 Data 期刊论文 REMOTE SENSING, 2019, 卷号: 11, 期号: 12 作者:  Zhang, Linjing;  Shao, Zhenfeng;  Liu, Jianchen;  Cheng, Qimin 收藏  |  浏览/下载：11/0  |  提交时间：2019/12/05 LiDAR  Landsat 8 OLI  combined optical and LiDAR indices  synergy  Stacked Sparse Autoencoder network (SSAE)  forest aboveground biomass (AGB)   Deep Learning Based Retrieval of Forest Aboveground Biomass from Combined LiDAR and Landsat 8 Data 期刊论文 REMOTE SENSING, 2019, 卷号: 11, 期号: 12 作者:  Zhang, Linjing;  Shao, Zhenfeng;  Liu, Jianchen;  Cheng, Qimin 收藏  |  浏览/下载：4/0  |  提交时间：2019/12/11 LiDAR  Landsat 8 OLI  combined optical and LiDAR indices  synergy  Stacked Sparse Autoencoder network (SSAE)  forest aboveground biomass  (AGB)   Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model for Hyperspectral Image Classification 期刊论文 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2019, 卷号: 57, 页码: 1741-1754 作者:  Deng, Cheng;  Xue, Yumeng;  Liu, Xianglong;  Li, Chao;  Tao, Dacheng 收藏  |  浏览/下载：15/0  |  提交时间：2019/12/30 Active learning (AL)  deep learning  hyperspectral image (HSI) classification  multiple-feature representation  stacked sparse autoencoder (SSAE)  transfer learning (TL)   Stacked Sparse Autoencoder Modeling Using the Synergy of Airborne LiDAR and Satellite Optical and SAR Data to Map Forest Above-Ground Biomass 期刊论文 IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2017, 卷号: 10, 期号: 12 作者:  Shao, Zhenfeng;  Zhang, Linjing;  Wang, Lei 收藏  |  浏览/下载：2/0  |  提交时间：2019/12/05 Biomass  deep learning (DL)  Landsat 8  light detection and ranging (LiDAR)  stacked sparse autoencoder network (SSAE)  Sentinel-1A   Assessment of PD severity in gas-insulated switchgear with an SSAE 期刊论文 IET SCIENCE MEASUREMENT & TECHNOLOGY, 2017, 卷号: 11, 期号: 4 作者:  Tang, Ju;  Jin, Miao;  Zeng, Fuping;  Zhang, Xiaoxing;  Huang, Rui 收藏  |  浏览/下载：7/0  |  提交时间：2019/12/05 partial discharge measurement  gas insulated switchgear  statistical analysis  neural nets  learning (artificial intelligence)  encoding  feature extraction  computerised instrumentation  PD severity assessment  gas-insulated switchgear  SSAE  partial discharge severity assessment  discharge time  discharge amplitude  deep-learning neural network model  stacked sparse autoencoder  feature extraction  soft-max classifier  unsupervised greedy layer-wise pre-training method  supervised fine-tuning method  support vector machine algorithm