AWhat changed
Proposed Fast R-CNN to train and evaluate region-based convolutional object detectors more efficiently through joint multi-task training.
Scientific scope
Proposed Fast R-CNN to train and evaluate region-based convolutional object detectors more efficiently through joint multi-task training. Scope limitation: Fast R-CNN refines earlier R-CNN and SPPnet approaches; it is distinct from the later Faster R-CNN region-proposal network.
Evidence
The retained primary-source abstract, bibliographic record and stated review scope support this provisional assessment. No independent experimental replication by WRS is claimed. Fast R-CNN refines earlier R-CNN and SPPnet approaches; it is distinct from the later Faster R-CNN region-proposal network.
Contributors
- The named authors listed in the linked research record · SCIENCE: Complete source byline retained in the research record; human research direction, method development and evaluation. Individual labor shares are not measured.
- Girshick: Fast R-CNN object detection — original paper
- Girshick: Fast R-CNN object detection — official Microsoft source
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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