Digital Image Processing, Third Edition
By R. González, R. Woods, B. Masters. 2009
1,448 citations recorded by the source corpus.
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Subfields: Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/15bd427a1a5f9bc57a7f67fb1b1fc85c5bb39f46
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In Radiology, Nuclear Medicine and Imaging
Citations in the corpus
- Deep learning for posture analysis in fall detection (2014, methodology): “We chose to use the method of deep learning for classification because of the following advantages: it provides richer imformation about the observed data by capturing interactions of many different factors on different levels through hierarchical learning and benefits from larger training sets.”
- Fast Normalized Cross-Correlation (2010, methodology): “For this reason normalized cross-correlation has been computed in the spatial domain (e.g., [ 7 ], p. 585).”
- A Computational Framework for Ultrastructural Mapping of Neural Circuitry (2009, methodology): “…(E, Ec), the glial Müller cell class (sQ), and the A thin 200-nm section was probed with anti-AGB IgGs after excitation of the rabbit retinal GC layer [60], visualized by silver-intensified immunogold detection [54], captured on a SyncroscanRT montaging system (182 nm/pixel), and aligned with…”
- Image phase shift invariance based cloud motion displacement vector calculation method for ultra-short-term solar PV power forecasting (2018, background): “grayscale value, and is the phase spectrum, which characterizes the spatial structure of the image [42].”