Reducing Training Data Using Pre-Trained Foundation Models: A Case Study on Traffic Sign Segmentation Using the Segment Anything Model

The utilization of robust, pre-trained foundation models enables simple adaptation to specific ongoing tasks. In particular, the recently developed Segment Anything Model (SAM) has demonstrated impressive results in the context of semantic segmentation. Recognizing that data collection is generally...

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Номзүйн дэлгэрэнгүй

Үндсэн зохиолчид:	Sofia Henninger, Maximilian Kellner, Benedikt Rombach, Alexander Reiterer
Формат:	Artigo
Хэл сонгох:	Inglês
Хэвлэсэн:	MDPI AG 2024-09-01
Цуврал:	Journal of Imaging
Нөхцлүүд:	semantic segmentation segment anything model Mask R-CNN training data reduction traffic signs
Онлайн хандалт:	https://www.mdpi.com/2313-433X/10/9/220
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!