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Multiple instance learning

Depending on the type and variation in training data, machine learning can be roughly categorized into three frameworks: supervised learning… 
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Related topics

Related topics

6 relations
Binary classificationBoosting (machine learning)Multi-label classificationMultiple-instance learning

Broader (1)

Machine learning

Papers overview

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2014
2014
Learning the object location, scale and view for image categorization with adapted classifier
2011
2011
Online multiple instance learning applied to hand detection in a humanoid robot
We propose an algorithm for the visual detection and localisation of the hand of a humanoid robot. This algorithm imposes low… 
2010
2010
Multiple instance learning for hyperspectral image analysis
Multiple instance learning is a recently researched learning paradigm that allows a machine learning algorithm to learn target… 
2010
2010
Inverse Multiple Instance Learning for Classifier Grids
Recently, classifier grids have shown to be a considerable alternative for object detection from static cameras. However, one… 
2010
2010
Local dimensionality reduction for multiple instance learning
Multiple instance learning involves labeling bags (sets of instances) rather than individual instances. Positive bags contain… 
2010
2010
A multiple instance learning based framework for semantic image segmentation
Most image segmentation algorithms extract regions satisfying visual uniformity criteria. Unfortunately, because of the semantic… 
2009
2009
Multiple instance and context dependent learning in hyperspectral data
Hyperspectral imaging (HSI) is a powerful tool for various remote sensing tasks including agricultural modeling and landmine… 
2007
2007
A Novel Multiple Instance Learning Approach for Image Retrieval Based on Adaboost Feature Selection
In image retrieval, the concepts are usually in region-level but annotated in image-level, which leads to a major difficulty in… 
2005
2005
Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years… 
2002
2002
User Concept Pattern Discovery Using Relevance Feedback And Multiple Instance Learning For Content-Based Image Retrieval
Understanding and learning the subjective aspect of humans in Content-Based Image Retrieval has been an active research field… 
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