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High- and low-level

Known as: High-level description, Low-level, High-level 
High-level and low-level are typically terms used to classify, describe and point to specific goals of a systematic operation, though its uses also… 
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Papers overview

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Highly Cited
2017
Highly Cited
2017
Feature pyramids are a basic component in recognition systems for detecting objects at different scales. But pyramid… 
Highly Cited
2011
Highly Cited
2011
Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale… 
Review
2011
Review
2011
  • W. Loh
  • WIREs Data Mining Knowl. Discov.
  • 2011
  • Corpus ID: 17654166
Classification and regression trees are machine‐learning methods for constructing prediction models from data. The models are… 
Highly Cited
2011
Highly Cited
2011
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max… 
Review
2010
Review
2010
Whereas before 2006 it appears that deep multilayer neural networks were not successfully trained, since then several algorithms… 
Highly Cited
2004
Highly Cited
2004
We describe a learning-based method for low-level vision problems—estimating scenes from images. We generate a synthetic world of… 
Highly Cited
2003
Highly Cited
2003
We present a method of learning a Bayesian model of a traveler moving through an urban environment. This technique is novel in… 
Highly Cited
2002
Highly Cited
2002
A general non-parametric technique is proposed for the analysis of a complex multimodal feature space and to delineate… 
Highly Cited
1999
Highly Cited
1999
We show a learning-based method for low-level vision problems-estimating scenes from images. We generate a synthetic world of… 
Review
1989
Review
1989
Starts with a brief review of the history and the application areas considered in the literature. The author then proceeds with…