This paper provides a comprehensive state-of-the-art investigation of the recent advances in
data science in emerging economic applications. The analysis is performed on the novel …

Multiple-instance learning has become popular over recent years due to its use in some
special scenarios. It is basically a type of weakly supervised learning where the learning …

Multiple instance learning (MIL) is a form of weakly supervised learning where training
instances are arranged in sets, called bags, and a label is provided for the entire bag. This …

Hyperspectral image classification has been acknowledged as the fundamental and
challenging task of hyperspectral data processing. The abundance of spectral and spatial …

Human action recognition is an active field of research in pattern recognition and computer
vision. For this purpose, several approaches based on bag-of-word features and support …

Multi-instance learning (MIL) has been widely applied to diverse applications involving
complicated data objects such as images and genes. However, most existing MIL algorithms …

Many real-world pattern recognition problems can be modeled using multiple-instance
learning (MIL), where instances are grouped into bags, and each bag is assigned a label …

In this paper, we address the problem of video temporal sentence localization, which aims to
localize a target moment from videos according to a given language query. We observe that …

With the rapid development of artificial intelligence (AI) concept technology, it promotes the
innovation of educational concept. Mostly for the education information analysis in the class …

Multi-instance learning (MIL) has been widely used on diverse applications involving
complicated data objects such as images, where people use a bag generator to represent …