Fully automatic figure‐ground segmentation algorithm based on deep convolutional neural network and GrabCut

Research article (IET Image Processing, 2016) · cited 15× · AI/ML
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Fully automatic figure‐ground segmentation algorithm based on deep convolutional neural network and GrabCut

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Fully automatic figure‐ground segmentation algorithm based on deep convolutional neural network and GrabCut is a scholarly article[1].

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  • Fully automatic figure‐ground segmentation algorithm based on deep convolutional neural network and GrabCut's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). Fully automatic figure‐ground segmentation algorithm based on deep convolutional neural network and GrabCut. Retrieved May 24, 2026, from https://4ort.xyz/entity/fully-automatic-figureground-segmentation-algorithm-based-on-deep-convolutional-neural-network-and-grabcut
MLA “Fully automatic figure‐ground segmentation algorithm based on deep convolutional neural network and GrabCut.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/fully-automatic-figureground-segmentation-algorithm-based-on-deep-convolutional-neural-network-and-grabcut.
BibTeX @misc{4ortxyz_fully-automatic-figureground-segmentation-algorithm-based-on-deep-convolutional-neural-network-and-grabcut_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Fully automatic figure‐ground segmentation algorithm based on deep convolutional neural network and GrabCut}}, year = {2026}, url = {https://4ort.xyz/entity/fully-automatic-figureground-segmentation-algorithm-based-on-deep-convolutional-neural-network-and-grabcut}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Fully automatic figure‐ground segmentation algorithm based on deep convolutional neural network and GrabCut — https://4ort.xyz/entity/fully-automatic-figureground-segmentation-algorithm-based-on-deep-convolutional-neural-network-and-grabcut (retrieved 2026-05-24)

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