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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… 
Wikipedia

Related topics

Related topics

21 relations
ALSAAnt colonyAssembly languageComplex system
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Broader (3)

CyberneticsFormal methodsSystems theory

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2017
Highly Cited
2017
Feature Pyramid Networks for Object Detection
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: Machine Learning in Python
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
Classification and regression trees
  • 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
Adaptive deconvolutional networks for mid and high level feature learning
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max… 
Review
2010
Review
2010
Understanding the difficulty of training deep feedforward neural networks
Whereas before 2006 it appears that deep multilayer neural networks were not successfully trained, since then several algorithms… 
Highly Cited
2004
Highly Cited
2004
Learning Low-Level Vision
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
Inferring High-Level Behavior from Low-Level Sensors
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
Mean Shift: A Robust Approach Toward Feature Space Analysis
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
Learning low-level vision
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
Petri nets: Properties, analysis and applications
Starts with a brief review of the history and the application areas considered in the literature. The author then proceeds with… 
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