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Depth Estimation and Semantic Segmentation from a Single RGB Image Using a Hybrid Convolutional Neur...

Depth Estimation and Semantic Segmentation from a Single RGB Image Using a Hybrid Convolutional Neur...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_71e935fa7eed45d5bbe19cc4dce54014

Depth Estimation and Semantic Segmentation from a Single RGB Image Using a Hybrid Convolutional Neural Network

About this item

Full title

Depth Estimation and Semantic Segmentation from a Single RGB Image Using a Hybrid Convolutional Neural Network

Publisher

Switzerland: Multidisciplinary Digital Publishing Institute (MDPI)

Journal title

Sensors (Basel, Switzerland), 2019-04, Vol.19 (8), p.1795

Language

English

Formats

Publication information

Publisher

Switzerland: Multidisciplinary Digital Publishing Institute (MDPI)

More information

Scope and Contents

Contents

Semantic segmentation and depth estimation are two important tasks in computer vision, and many methods have been developed to tackle them. Commonly these two tasks are addressed independently, but recently the idea of merging these two problems into a sole framework has been studied under the assumption that integrating two highly correlated tasks...

Alternative Titles

Full title

Depth Estimation and Semantic Segmentation from a Single RGB Image Using a Hybrid Convolutional Neural Network

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_71e935fa7eed45d5bbe19cc4dce54014

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_71e935fa7eed45d5bbe19cc4dce54014

Other Identifiers

ISSN

1424-8220

E-ISSN

1424-8220

DOI

10.3390/s19081795

How to access this item