Deep-learning-based information mining from ocean remote-sensing imagery
文献类型：CNKI期刊论文
| 作者 | Xiaofeng Li; Bin Liu; Gang Zheng; Yibin Ren; Shuangshang Zhang; Yingjie Liu; Le Gao; Yuhai Liu; Bin Zhang; Fan Wang
|
| 发表日期 | 2020-10-20 |
| 出处 | National Science Review
 |
| 关键词 | ocean remote sensing big data artificial intelligence image classification |
| 英文摘要 | With the continuous development of space and sensor technologies during the last 40 years, ocean remote sensing has entered into the big-data era with typical five-V(volume, variety, value, velocity and veracity)characteristics. Ocean remote-sensing data archives reach several tens of petabytes and massive satellite data are acquired worldwide daily. To precisely, efficiently and intelligently mine the useful information submerged in such ocean remote-sensing data sets is a big challenge. Deep learning—a powerful technology recently emerging in the machine-learning field—has demonstrated its more significant superiority over traditional physical-or statistical-based algorithms for image-information extraction in many industrial-field applications and starts to draw interest in ocean remote-sensing applications. In this review paper, we first systematically reviewed two deep-learning frameworks that carry out ocean remote-sensing-image classifications and then presented eight typical applications in ocean internal-wave/eddy/oil-spill/coastal-inundation/sea-ice/green-algae/ship/coral-reef mapping from different types of ocean remote-sensing imagery to show how effective these deep-learning frameworks are. Researchers can also readily modify these existing frameworks for information mining of other kinds of remote-sensing imagery. |
| 文献子类 | CNKI期刊论文 |
| 资助机构 | supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19060101 and XDA19090103) ; the Senior User Project of RV KEXUE,managed by the Center for Ocean Mega-Science,Chinese Academy of Sciences (KEXUE2019GZ04) ; the Key R&D Project of Shandong Province (2019JZZY010102) ; the Key Deployment Project of Center for Ocean Mega-Science,CAS(COMS2019R02) ; the CAS Program (Y9KY04101L) ; the China Postdoctoral Science Foundation (2019M651474 and 2019M662452) |
| 卷 | v.7期:10页:70-91 |
| 语种 | 英文; |
| 分类号 | TP18;TP751;P714 |
| ISSN号 | 2095-5138 |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/187974]  |
| 专题 | 中国科学院海洋研究所 |
| 作者单位 | 1.KeyLaboratoryofOceanCirculationandWaves,InstituteofOceanology,ChineseAcademyofSciences 2.CenterforOceanMega-Science,ChineseAcademyofSciences 3.CollegeofMarineSciences,ShanghaiOceanUniversity 4.StateKeyLaboratoryofSatelliteOceanEnvironmentDynamics,SecondInstituteofOceanography,MinistryofNaturalResources 5.CollegeofOceanography,HohaiUniversity 6.DawningInternationalInformationIndustryCo.,Ltd. |
| 推荐引用方式 GB/T 7714 | Xiaofeng Li,Bin Liu,Gang Zheng,et al. Deep-learning-based information mining from ocean remote-sensing imagery. 2020. |
入库方式： OAI收割
来源：海洋研究所
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