| 查看: 7539 | 回复: 2919 | |||||
[交流]
【2016-06-01】【SCI 检索】Machine Learning Methods for Remote Sensing Image
|
|||||
Springer系列SCI期刊 “Multimedia Tools and Applications”的专刊，不交版面费，已经可以投稿。有任何疑问请回复此贴咨询。 Multimedia Tools and Applications：Special Issue on Advanced Machine Learning Methods for Remote Sensing Image Processing Guest Editors Peng Liu, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.R. China, liupeng@radi.ac.cn Lizhe Wang, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.R. China, Lizhe.Wang@computer.org CALL FOR PAPERS We have entered an era of big data. The requirements of different investigations have increased the specialization and diversity of techniques of acquiring remote sensing image. We can take them as a new type of multimedia data. Remote sensing image often differ features in terms of their resolution, revisit cycle, spectrum, and mode of imaging. It is popular to refer to the three Vs when characterizing big data: remarkable growths in the volume, velocity and variety of data. However, remote sensing image big data has several concrete and special characteristics: multi-source, multi-scale, high dimensional, dynamic-state, isomer, and non-linear characteristics. There is no doubt that existing techniques and methods are too limited to solve all the problems of remote-sensing image data completely. Therefore, more advanced methods are required to find the implicit law hidden within the remote-sensing image. In recent years, machine learning methods play an essential role in the data analysis of remote sensing, including image classification, image segmentation, registration and fusion, target detection, information retrieval, etc. Due to large variations and complexity of the in space and time, it is typically difficult to derive analytical solutions or formulations to represent characteristic and changing in the surface of the earth based on remote sensing data. Researchers are now beginning to adapt advanced modern machine learning and pattern recognition techniques, such as manifold learning, sparse representation, low-rank presentation, compressive sensing and deep learning, to solve related problems in the complex remote sensing data. The main scope of this special issue is to help boost the scientific research within the broad field of machine learning in the remote sensing image data. This special issue will focus on major trends and challenges in this area, and will present work aimed to identify new cutting-edge research and their applications in remote sensing images. The topics of interest for this special issue include, but are not limited to: Machine Learning theories such as SVM, low rank, compressive sensing, sparse coding, transfer learning and deep learning and etc. Correlativity analysis for remote sensing image Correlativity analysis for GIS data Reconstruction of remote sensing image Fusion of remote sensing data Classification based on remote sensing image Change detection based on spatial-temporal remote sensing image Sparse representation of remote sensing image Dimension reduction for remote sensing data High performance computing for complex remote sensing data Computing vision and target detection based on remote sensing image Applications based on remote sensing image, such as agriculture, environment, land cover, hydrology and etc. Data visualization and analysis for GIS and remote sensing data Important Date Open for submissions: Already Open Closed for submissions: June 1st, 2016 Results of first round of reviews: Sep 1st, 2016 Submission of revised manuscripts: Nov. 1st, 2016 Final decision: Dec. 31th, 2016 关于投稿： Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by, other journals. Springer offers authors, editors and reviewers of Multimedia Tools and Applications journal a web-enabled online manuscript submission and review system. Our online system offers authors the ability to track the review process of their manuscript. Manuscripts should be submitted to: http://MTAP.edmgr.com. This online system offers easy and straightforward log-in and submission procedures, and supports a wide range of submission file formats. All papers will be peer-reviewed following the Multimedia Tools and Applications reviewing procedures. Authors should prepare their manuscripts according to the online submission page of Multimedia Tools and Applications at www.Springer.com/11042 http://www.springer.com/journal/11042 [ Last edited by GuestEditor on 2016-1-22 at 14:32 ] |
回复此楼» 本帖@通知
» 猜你喜欢
有没有在职教师同时做博后的？
已经有4人回复
-
word转成pdf之后公式里面的字体变了，正文字体没变。
已经有10人回复
-
想被211以上高校课题组接收
已经有13人回复
-
国自然的面上项目，５个审稿人，５个B能上会吗？
已经有29人回复
-
博士去高校就是为了有寒暑假吗？
已经有28人回复
-
为什么有的影响因子高的期刊分区不高呢？
已经有4人回复
-
超过35岁的海外博士还可以进高校吗？
已经有5人回复
-
审不上青基又非升即走的青椒 和 牢里踩缝纫机的犯人哪个活的更舒服一点？
已经有19人回复
-
经常觉得挺累的
已经有3人回复
-
人生
已经有7人回复
» 抢金币啦！回帖就可以得到:
-
西安“石油地质研究实验室”18791013812田老师
+1/98
-
欢迎加入浙江大学生物系统工程与食品科学学院-农产品加工新技术装备课题组！
+1/87
-
测试█TEM/ EPR/ XPS/PY-GCMS/TPD/SEM/XRF/BET/MIP/核磁/EA/ICP，VX: 761711562。
+1/83
-
大湾区大学（筹）李忠良团队40-45万年薪诚聘有机合成博士后
+1/81
-
大湾区大学（筹）-中科大年薪55万联合招聘光催化方向博士后
+1/81
-
大湾区大学（筹）-中科大年薪55万联合招聘光催化方向博士后
+1/78
-
90后男北京真诚征婚 (征到即删，长期有效)
+1/68
-
90后男北京真诚征婚 (征到即删，长期有效)
+1/65
-
微纳光学、光电集成、超表面、热辐射、二维材料、钙钛矿等方向招博士后、研究助理教授
+1/44
-
50万起年薪诚聘骨科基础研究方向博后，上不封顶
+2/36
-
中国科学院过程工程研究所能源与环境催化课题组招聘研究助理启事
+1/32
-
中国科学院过程工程研究所能源与环境催化课题组招聘研究助理启事
+1/29
-
双一流高校国家优青课题组招聘教师-博后-科研助理（本帖长期有效）
+1/9
-
jade能够只更新pdf卡片库不更新jade软件？
+1/8
-
海南大学光电功能分子基材料课题组招聘师资博后
+1/8
-
澳门大学诚聘博后、博士和硕士研究生
+1/7
-
北京市事业单位：2024年度中国科学技术信息研究所招聘博士后（长期有效）
+1/4
-
《振动与冲击》投稿交流
+1/3
-
清华大学深圳国际研究生院-周学拳课题组诚聘博士后/科研助理/硕博
+1/2
-
求NSGA-III matlab代码
+1/1
+1/98
22楼2016-01-14 14:35:41
简单回复
天涯sx2楼
2016-01-14 14:04
回复
GuestEditor(金币+1): 谢谢参与
小凡下山3楼
2016-01-14 14:05
回复
GuestEditor(金币+1): 谢谢参与
yuzhuce4楼
2016-01-14 14:16
回复
GuestEditor(金币+1): 谢谢参与
woodyjun5楼
2016-01-14 14:21
回复
GuestEditor(金币+1): 谢谢参与
2016-01-14 14:23
回复
GuestEditor(金币+1): 谢谢参与
fdzjm7楼
2016-01-14 14:23
回复
GuestEditor(金币+1): 谢谢参与
假大空8楼
2016-01-14 14:24
回复
GuestEditor(金币+1): 谢谢参与
纳米材料7539楼
2016-01-14 14:26
回复
GuestEditor(金币+1): 谢谢参与
clszdy10楼
2016-01-14 14:26
回复
GuestEditor(金币+1): 谢谢参与
liqingbiao11楼
2016-01-14 14:26
回复
GuestEditor(金币+1): 谢谢参与
liuges12楼
2016-01-14 14:28
回复
GuestEditor(金币+1): 谢谢参与
meixiangwq13楼
2016-01-14 14:28
回复
GuestEditor(金币+1): 谢谢参与
祝福
taoxim14楼
2016-01-14 14:28
回复
GuestEditor(金币+1): 谢谢参与
祝福
tangfeng201615楼
2016-01-14 14:32
回复
GuestEditor(金币+1): 谢谢参与
wh201416楼
2016-01-14 14:33
回复
GuestEditor(金币+1): 谢谢参与
zl821366217楼
2016-01-14 14:34
回复
GuestEditor(金币+1): 谢谢参与
nieliangl18楼
2016-01-14 14:35
回复
GuestEditor(金币+1): 谢谢参与
祝福
hodydo19楼
2016-01-14 14:35
回复
GuestEditor(金币+1): 谢谢参与
祝福
lengshuk20楼
2016-01-14 14:35
回复
GuestEditor(金币+1): 谢谢参与
祝福
吉海21楼
2016-01-14 14:35
回复
GuestEditor(金币+1): 谢谢参与
liuzhuit23楼
2016-01-14 14:35
回复
GuestEditor(金币+1): 谢谢参与
祝福
coco8624楼
2016-01-14 14:35
回复
GuestEditor(金币+1): 谢谢参与
wanghuap25楼
2016-01-14 14:35
回复
GuestEditor(金币+1): 谢谢参与
祝福
yongxiny26楼
2016-01-14 14:36
回复
GuestEditor(金币+1): 谢谢参与
linxuyue27楼
2016-01-14 14:36
回复
GuestEditor(金币+1): 谢谢参与
祝福
御龙12328楼
2016-01-14 14:36
回复
GuestEditor(金币+1): 谢谢参与
ningkongt29楼
2016-01-14 14:36
回复
GuestEditor(金币+1): 谢谢参与
piaozhoup30楼
2016-01-14 14:36
回复
GuestEditor(金币+1): 谢谢参与
支持
kafdyu31楼
2016-01-14 14:36
回复
GuestEditor(金币+1): 谢谢参与
Emperor翔32楼
2016-01-14 14:36
回复
GuestEditor(金币+1): 谢谢参与
1
kolimm33楼
2016-01-14 14:36
回复
GuestEditor(金币+1): 谢谢参与
.
sunnaiv34楼
2016-01-14 14:36
回复
GuestEditor(金币+1): 谢谢参与
祝福
怕黑的猫头鹰35楼
2016-01-14 14:37
回复
GuestEditor(金币+1): 谢谢参与
星尘飞扬36楼
2016-01-14 14:37
回复
GuestEditor(金币+1): 谢谢参与
祝福
am435937楼
2016-01-14 14:37
回复
GuestEditor(金币+1): 谢谢参与
。
peaceearth38楼
2016-01-14 14:37
回复
GuestEditor(金币+1): 谢谢参与
小坏蛋66639楼
2016-01-14 14:37
回复
GuestEditor(金币+1): 谢谢参与
matianvc40楼
2016-01-14 14:38
回复
GuestEditor(金币+1): 谢谢参与
vdmxmb41楼
2016-01-14 14:38
回复
GuestEditor(金币+1): 谢谢参与
.
zhoushanqun42楼
2016-01-14 14:38
回复
GuestEditor(金币+1): 谢谢参与
mahongj43楼
2016-01-14 14:38
回复
GuestEditor(金币+1): 谢谢参与
祝福
bincmq44楼
2016-01-14 14:38
回复
GuestEditor(金币+1): 谢谢参与
hehunw45楼
2016-01-14 14:38
回复
GuestEditor(金币+1): 谢谢参与
欢仔子46楼
2016-01-14 14:38
回复
GuestEditor(金币+1): 谢谢参与
vcokcb47楼
2016-01-14 14:39
回复
GuestEditor(金币+1): 谢谢参与
mv973848楼
2016-01-14 14:39
回复
GuestEditor(金币+1): 谢谢参与
韩松帅49楼
2016-01-14 14:39
回复
GuestEditor(金币+1): 谢谢参与
祝福
spc0850楼
2016-01-14 14:39
回复
GuestEditor(金币+1): 谢谢参与
