8 citations · 10 across the 5 of their papers we have counts for
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cs.CV2017
Image Super-resolution via Feature-augmented Random Forest
Hailiang Li, Kin-Man Lam, Miaohui Wang
Recent random-forest (RF)-based image super-resolution approaches inherit some properties from dictionary-learning-based algorithms, but the effectiveness of the properties in RF i…
cs.CV2017★ 2 cited
Joint Maximum Purity Forest with Application to Image Super-Resolution
Hailiang Li, Kin-Man Lam, Dong Li
In this paper, we propose a novel random-forest scheme, namely Joint Maximum Purity Forest (JMPF), for classification, clustering, and regression tasks. In the JMPF scheme, the ori…