Faster R-CNN
Faster R-CNN je dvofazni duboki konvolucioni okvir za detekciju objekata koji su predstavili Shaoqing Ren, Kaiming He, Ross Girshick i Jian Sun (Microsoft Research) na NeurIPS-u 2015. On zamenjuje spor korak predlaganja regiona selektivnom pretragom (selective-search region proposal) koji se koristio u njegovim prethodnicima R-CNN i Fast R-CNN sa naučenom mrežom za predlaganje regiona (Region Proposal Network – RPN) koja deli konvolucione karakteristike sa detekcionom glavom, omogućavajući prvi end-to-end obučivi, skoro real-time precizan detektor objekata i uspostavljajući dugotrajni reper tačnosti na PASCAL VOC i MS COCO skupovima podataka.
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Izvori
- Ren, S., He, K., Girshick, R., & Sun, J. (2015). Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. Advances in Neural Information Processing Systems (NeurIPS), 28, 91–99. link ↗
- Ren, S., He, K., Girshick, R., & Sun, J. (2017). Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(6), 1137–1149. DOI: 10.1109/TPAMI.2016.2577031 ↗
- Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning (Ch. 9: Convolutional Networks). MIT Press. ISBN: 978-0-262-03561-3
Kako citirati ovu stranicu
ScholarGate. (2026, June 3). Faster Region-based Convolutional Neural Network. ScholarGate. https://scholargate.app/sr/deep-learning/faster-r-cnn
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Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- ResNet (Rezidualna Mreža)Duboko učenje↔ compare
- YOLO (You Only Look Once)Duboko učenje↔ compare
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