In online tracking, the tracker evolves to reflect variations in object appearance and surroundings. This updating process is formulated as a supervised learning problem, thus a ...
We propose using multi-layer multiple instance learning (MMIL) for image set classification and applying it to the task of cannabis website classification. We treat each image as a...
An innovative technique based on multi-objective grammar guided genetic programming (MOG3P-MI) is proposed to detect the most relevant activities that a student needs to pass a cou...
Abstract--Multiple instance learning (MIL) is a recently researched technique used for learning a target concept in the presence of noise. Previously, a random set framework for mu...
In this article, we describe a feature selection algorithm which can automatically find relevant features for multiple instance learning. Multiple instance learning is considered a...
Pedestrian detection in still image should handle the large appearance and stance variations arising from the articulated structure, various clothing of human as well as viewpoints...
In this paper we present a boosting approach to multiple instance learning. As weak hypotheses we use balls (with respect to various metrics) centered at instances of positive bags...
Abstract. This paper introduces the use of multi-objective evolutionary algorithms in multiple instance learning. In order to achieve this purpose, a multi-objective grammar-guided...