Machine Learning In Problems Involved In Processing Satellite Images.
Saved in:
| Title: | Machine Learning In Problems Involved In Processing Satellite Images. |
|---|---|
| Authors: | Bass, L. P.1 (AUTHOR) lpb1911@yandex.ru, Plastinin, Yu. A.2 (AUTHOR), Skryabysheva, I. Yu.2 (AUTHOR) |
| Source: | Measurement Techniques. Mar2021, Vol. 63 Issue 12, p950-958. 9p. |
| Subjects: | Remote-sensing images, Machine learning, Convolutional neural networks, Artificial neural networks, Telecommunication satellites |
| Abstract: | The use of a machine (computer) vision system for remove probing of the Earth is considered. A survey of software and hardware methods used in computer vision systems in the processing of satellite images is presented. Methods of processing data with the use of a trained neural network are described. Examples of algorithmic processing of satellite images by means of artificial convolutional neural networks are presented. Methods of increasing the precision of recognition of satellite images are determined. Practical applications of convolutional neural networks onboard microsatellites used for remote probing of the Earth are presented. [ABSTRACT FROM AUTHOR] |
| Copyright of Measurement Techniques is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 149961153 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Machine Learning In Problems Involved In Processing Satellite Images. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Bass%2C+L%2E+P%2E%22">Bass, L. P.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> lpb1911@yandex.ru</i><br /><searchLink fieldCode="AR" term="%22Plastinin%2C+Yu%2E+A%2E%22">Plastinin, Yu. A.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Skryabysheva%2C+I%2E+Yu%2E%22">Skryabysheva, I. Yu.</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Measurement+Techniques%22">Measurement Techniques</searchLink>. Mar2021, Vol. 63 Issue 12, p950-958. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Remote-sensing+images%22">Remote-sensing images</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Convolutional+neural+networks%22">Convolutional neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Telecommunication+satellites%22">Telecommunication satellites</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The use of a machine (computer) vision system for remove probing of the Earth is considered. A survey of software and hardware methods used in computer vision systems in the processing of satellite images is presented. Methods of processing data with the use of a trained neural network are described. Examples of algorithmic processing of satellite images by means of artificial convolutional neural networks are presented. Methods of increasing the precision of recognition of satellite images are determined. Practical applications of convolutional neural networks onboard microsatellites used for remote probing of the Earth are presented. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Measurement Techniques is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=149961153 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11018-021-01877-6 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 950 Subjects: – SubjectFull: Remote-sensing images Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Convolutional neural networks Type: general – SubjectFull: Artificial neural networks Type: general – SubjectFull: Telecommunication satellites Type: general Titles: – TitleFull: Machine Learning In Problems Involved In Processing Satellite Images. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Bass, L. P. – PersonEntity: Name: NameFull: Plastinin, Yu. A. – PersonEntity: Name: NameFull: Skryabysheva, I. Yu. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 05431972 Numbering: – Type: volume Value: 63 – Type: issue Value: 12 Titles: – TitleFull: Measurement Techniques Type: main |
| ResultId | 1 |
