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东海海域米氏凯伦藻和东海原甲藻的分布特征及其影响因素研究 学位论文
, 中国科学院海洋研究所: 中国科学院大学, 2022
Authors:  胡晓坤
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东海  有害藻华  米氏凯伦藻  东海原甲藻  qPCR  
南海 F 冷泉生态系统大型底栖动物群落特征与食物网分析 学位论文
理学博士, 中国科学院海洋研究所: 中国科学院大学, 2022
Authors:  王海宁
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冷泉  大型底栖动物  物种多样性  营养关系  深度学习  
《海洋科学快报》2022年第16期 其他
2022-05-05
Authors:  《海洋科学快报》编辑部
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凡纳滨对虾生长和耐高盐性状相关标记的筛选及基因组育种技术研究 学位论文
理学博士, 中国科学院海洋研究所: 中国科学院大学, 2022
Authors:  罗正
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全基因组关联分析  基因组选择  生长性状  耐高盐性状  凡纳滨对虾  
无人机低空遥感在大型水母和海滩垃圾监测中的应用 学位论文
, 中国科学院海洋研究所: 中国科学院大学, 2022
Authors:  邱琰皓
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无人机,低空遥感,大型水母,海滩垃圾,监测  
Reconstruction of global surface ocean pCO(2) using region-specific predictors based on a stepwise FFNN regression algorithm 期刊论文
BIOGEOSCIENCES, 2022, 卷号: 19, 期号: 3, 页码: 845-859
Authors:  Zhong, Guorong;  Li, Xuegang;  Song, Jinming;  Qu, Baoxiao;  Wang, Fan;  Wang, Yanjun;  Zhang, Bin;  Sun, Xiaoxia;  Zhang, Wuchang;  Wang, Zhenyan;  Ma, Jun;  Yuan, Huamao;  Duan, Liqin
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Experimental Study on the Influence of Flexible Control on Key Parameters in Reverse Osmosis Desalination 期刊论文
IEEE ACCESS, 2022, 卷号: 10, 页码: 4844-4860
Authors:  Chu, Shuai;  Zhang, Shitan;  Ma, Xiaona;  Li, Yinxuan;  Qiu, Denggao;  Ge, Weichun;  Kou, Lei
Adobe PDF(3596Kb)  |  Favorite  |  View/Download:21/0  |  Submit date:2022/02/21
Desalination  Feeds  Energy consumption  Reverse osmosis  Production  Bars  Synchronous motors  Reverse osmosis  variable-frequency drive  specific energy consumption  recovery rate  power frequency  
Tropical Cyclone Intensity Estimation From Geostationary Satellite Imagery Using Deep Convolutional Neural Networks 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60, 页码: 16
Authors:  Wang, Chong;  Zheng, Gang;  Li, Xiaofeng;  Xu, Qing;  Liu, Bin;  Zhang, Jun
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Estimation  Ocean temperature  Clouds  Tropical cyclones  Cyclones  Training  Geostationary satellites  Convolutional neural network (CNN)  deep learning  remote sensing  tropical cyclone (TC)  
A Deep Learning Model to Extract Ship Size From Sentinel-1 SAR Images 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60, 页码: 14
Authors:  Ren, Yibin;  Li, Xiaofeng;  Xu, Huan
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Marine vehicles  Radar polarimetry  Feature extraction  Synthetic aperture radar  Data mining  Radar imaging  Oceans  Custom loss function  deep learning (DL)  deep neural network (DNN) regression  ship size extraction  synthetic aperture radar (SAR) image  
Development of a Dual-Attention U-Net Model for Sea Ice and Open Water Classification on SAR Images 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 卷号: 19, 页码: 5
Authors:  Ren, Yibin;  Li, Xiaofeng;  Yang, Xiaofeng;  Xu, Huan
Adobe PDF(8369Kb)  |  Favorite  |  View/Download:21/0  |  Submit date:2022/02/18
Sea ice  Radar polarimetry  Feature extraction  Decoding  Oceans  Kernel  Image segmentation  Dual-attention  sea ice and open water classification  synthetic aperture radar (SAR) image  U-Net