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Takeda adaptive kernel regression
Adaptive Kernel Regression, supplied by Takeda, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/adaptive+kernel+regression/adaptive+kernel+regression/10__1049_slash_iet___ipr__2018__5857-45-30-24
Average 90 stars, based on 1 article reviews
adaptive kernel regression - by Bioz Stars, 2026-09
90/100 stars

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Article Title: Static and space-time visual saliency detection by self-resemblance.
Article Snippet: The original motivation behind these contributions is the earlier work on adaptive kernel regression for image and video reconstruction (Takeda, Farsiu, & Milanfar, 2007; Takeda, Milanfar, Protter, & Elad, 2009) and nonparametric object detection (Seo & Milanfar, 2009a) and action recognition (available online from http://users.soe.ucsc.edu/~milanfar/ publications; Seo & Milanfar, under review).

Article Title: Fabric defect detection using saliency of multi‐scale local steering kernel
Article Snippet: Inspired by the success of saliency application, we propose a novel FDD method via the saliency analysis, which is motivated by the work of Takeda et al. [37] where the adaptive kernel regression is used for image processing and reconstruction.

Article Title: Detecting Default Mode Networks in Utero by Integrated 4D fMRI Reconstruction and Analysis
Article Snippet: To account for this problem, we incorporate adaptive kernel regression to extend the support for the kernel to contain adequate samples ( Pham and Vliet 2003 ; Takeda et al. 2007 ).

Article Title: Super-resolving blurry multiframe images through multiframe blind deblurring using ADMM
Article Snippet: Multiframe super resolution (MFSR) aims to reconstruct a high resolution (HR) image from a set of low resolution (LR) images.. However, the MFSR is an ill-posed problem and typically computational costly.. In this paper, we propose to super-resolve multiple degraded LR frames of the original scene through multiframe blind deblurring (MFDB).



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