Image classification is a critical and meaningful task in image retrieval, recognition and
object detection. In this paper, three-side efforts are taken to accomplish this task. First …

In this paper, a novel multi-instance learning (MIL) algorithm based on multiple-kernels (MK)
framework has been proposed for image classification. This newly developed algorithm …

Multiple instance learning (MIL) has been proposed to classify the bag of instances. In
practice, we may meet the problems which have more than one view data. For example, in …

Multi-instance learning (MIL) is a special kind of classification problem where samples
(called “instances”) are grouped into bags and labels are given only on bag level instead of …

In this paper, we propose a novel method based on sparse coding and classifier ensemble
for tackling image categorization problem under the framework of multi-instance learning …

Abstract When applying Multiple Instance Learning (MIL) for image categorization, an image
is treated as a bag containing a number of instances, each representing a region inside the …

Abstract Multiple Instance Learning (MIL) has been widely used in various applications
including image classification. However, existing MIL methods do not explicitly address the …

Diverse applications involving complicated data objects such as proteins and images are
solved by applying multi-instance learning (MIL) algorithms. However, few MIL algorithms …

In multi-instance learning, the training examples are bags composed of instances without
labels, and the task is to predict the labels of unseen bags through analyzing the training …

Abstract Multiple Instance Learning (MIL) is a popular learning technique in various vision
tasks including image classification. However, most existing MIL methods do not consider …