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Teeth segmentation by optical radiographic images using VGG-16 deep learning convolution architecture with R-CNN network approach for biomedical sensing applications
Research article (Optical and Quantum Electronics, 2023) · cited 10× · AI/ML
Teeth segmentation by optical radiographic images using VGG-16 deep learning convolution architecture with R-CNN network approach for biomedical sensing applications
Summary
Teeth segmentation by optical radiographic images using VGG-16 deep learning convolution architecture with R-CNN network approach for biomedical sensing applications is a scholarly article[1].
Key Facts
Teeth segmentation by optical radiographic images using VGG-16 deep learning convolution architecture with R-CNN network approach for biomedical sensing applications's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Teeth segmentation by optical radiographic images using VGG-16 deep learning convolution architecture with R-CNN network approach for biomedical sensing applications. Retrieved May 24, 2026, from https://4ort.xyz/entity/teeth-segmentation-by-optical-radiographic-images-using-vgg-16-deep-learning-convolution-architecture-with-r-cnn-network
MLA“Teeth segmentation by optical radiographic images using VGG-16 deep learning convolution architecture with R-CNN network approach for biomedical sensing applications.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/teeth-segmentation-by-optical-radiographic-images-using-vgg-16-deep-learning-convolution-architecture-with-r-cnn-network.
BibTeX@misc{4ortxyz_teeth-segmentation-by-optical-radiographic-images-using-vgg-16-deep-learning-convolution-architecture-with-r-cnn-network_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Teeth segmentation by optical radiographic images using VGG-16 deep learning convolution architecture with R-CNN network approach for biomedical sensing applications}}, year = {2026}, url = {https://4ort.xyz/entity/teeth-segmentation-by-optical-radiographic-images-using-vgg-16-deep-learning-convolution-architecture-with-r-cnn-network}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Teeth segmentation by optical radiographic images using VGG-16 deep learning convolution architecture with R-CNN network approach for biomedical sensing applications — https://4ort.xyz/entity/teeth-segmentation-by-optical-radiographic-images-using-vgg-16-deep-learning-convolution-architecture-with-r-cnn-network (retrieved 2026-05-24)
