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A Refined and Efficient CNN Algorithm for Remote Sensing Object Detection

A Refined and Efficient CNN Algorithm for Remote Sensing Object Detection

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_41e3ff085fcb4e7e99314c54496df9b9

A Refined and Efficient CNN Algorithm for Remote Sensing Object Detection

About this item

Full title

A Refined and Efficient CNN Algorithm for Remote Sensing Object Detection

Publisher

Switzerland: MDPI AG

Journal title

Sensors (Basel, Switzerland), 2024-11, Vol.24 (22), p.7166

Language

English

Formats

Publication information

Publisher

Switzerland: MDPI AG

More information

Scope and Contents

Contents

Remote sensing object detection (RSOD) plays a crucial role in resource utilization, geological disaster risk assessment and urban planning. Deep learning-based object-detection algorithms have proven effective in remote sensing image studies. However, accurate detection of objects with small size, dense distribution and complex object arrangement...

Alternative Titles

Full title

A Refined and Efficient CNN Algorithm for Remote Sensing Object Detection

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_41e3ff085fcb4e7e99314c54496df9b9

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_41e3ff085fcb4e7e99314c54496df9b9

Other Identifiers

ISSN

1424-8220

E-ISSN

1424-8220

DOI

10.3390/s24227166

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