Object detection using YOLO: challenges, architectural successors, datasets and applications
Object detection using YOLO: challenges, architectural successors, datasets and applications
About this item
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Publisher
New York: Springer US
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Language
English
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Publisher
New York: Springer US
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Scope and Contents
Contents
Object detection is one of the predominant and challenging problems in computer vision. Over the decade, with the expeditious evolution of deep learning, researchers have extensively experimented and contributed in the performance enhancement of object detection and related tasks such as object classification, localization, and segmentation using u...
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Full title
Object detection using YOLO: challenges, architectural successors, datasets and applications
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9358372
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9358372
Other Identifiers
ISSN
1380-7501
E-ISSN
1573-7721
DOI
10.1007/s11042-022-13644-y
