Jul 29, 2009 · In this paper, we propose a novel learning technique which transforms the MIL problem into a standard supervised learning problem by defining a feature vector ...
In this paper, we propose a novel learning technique which transforms the MIL problem into a standard supervised learning problem by defining a feature vector ...
TL;DR: A novel learning technique is proposed which transforms the MIL problem into a standard supervised learning problem by defining a feature vector for ...
Hao Cheng, Kien A. Hua, Ning Yu: An automatic feature generation approach to multiple instance learning and its applications to image databases.
For each example image, a bag of multiple instances are obtained by choosing different sub-regions of the image and generating a feature vector for each region.
Both multiple-instance learning and active learning are widely employed in image categorization, but generally they are applied separately.
Image Categorization by Learning and Reasoning with Regions
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This paper presents a new learning technique, which extends Multiple-Instance Learning (MIL), and its application to the problem of region-based image ...
In this study we present FGSES, a general framework for automatic feature engineering and its application to DBpedia.
The multiple-instance learning model has received much attention recently with a primary application area being that of drug activity prediction.
Nov 18, 2007 · An automatic feature generation approach to multiple instance learning and its applications to image databases. Automatic content-based image ...