faster-r-cnn-towards-real-time-object-detection-with-region-proposal-networks-2021-024

Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun

0 Est. reading time9 views0 downloads0 reviews

Verified repository recordMetadataMetadata 90%Repository readiness 92%

faster-r-cnn-towards-real-time-object-detection-with-region-proposal-networks-2021-024

Shaoqing Ren, Kaiming He, Ross Girshick, Jian SunUFTAN UNIVERSITYElectrical and Electronics Engineering2021

Abstract

This record links to the Faster R-CNN paper, which introduces region proposal networks for efficient object detection. It is suitable for testing robotics, intelligent systems, and engineering repository metadata.

Metadata

Author: Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun
Supervisor: Dr. Patricia C. Nnamdi
Faculty: Engineering
Department: Electrical and Electronics Engineering
Document type: Masters Thesis
Year: 2021
Keywords: Faster R-CNN, object detection, region proposal networks, computer vision, real time detection
Access: Metadata
License: all_rights_reserved

Cite this work

Auto-generated from the record metadata: authors, journal title, DOI, volume, issue/serial, pages and publication date. Review before final academic use.

Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun (2026). faster-r-cnn-towards-real-time-object-detection-with-region-proposal-networks-2021-024 [Masters Thesis]. UFTAN UNIVERSITY. https://inrepscholar.com/uftan-university/projects/963

Source fields used: Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun

Export citation and metadata

APA RIS BibTeX Dublin Core DataCite

Academic reviews

No approved reviews yetReviews and citation feedback appear here after moderation.

Sign in to submit a review or correction suggestion for this record.

faster-r-cnn-towards-real-time-object-detection-with-region-proposal-networks-2021-024

Abstract

Metadata

Cite this work

Academic reviews

Related records