Recognizing multiple labels of an image is a practical yet challenging task, and remarkable
progress has been achieved by searching for semantic regions and exploiting label …

Scene classification is a significant aspect of computer vision. Convolutional neural
networks (CNNs), a development of deep learning, are a well-understood tool for image …

In this paper, we present a feature description method called semantic descriptor with
objectness (SDO) for scene recognition. Most existing scene representation methods exploit …

Metric learning can be very useful to improve the performance of a distance-dependent
classifier. However, separating metric learning from the classifier learning possibly …

Metric learning aims to learn an appropriate distance metric for a given machine learning
task. Despite its impressive performance in the field of image recognition, it may still not be …

Part model-based methods have been successfully applied to object detection and scene
classification and have achieved state-of-the-art results. More recently the" sparselets" work …

Learning domain adaptive features aims to enhance the classification performance of the
target domain by exploring the discriminant information from an auxiliary source set. Let X …

Scene recognition plays an important role in many computer vision tasks. However, the
recognition performance hardly meets the development of computer vision, since scene …

Pedestrian detection is an important example of object detection and has attracted much
attention. Many works have shown that good image features provide high detection …

In view of the scene's complexity and diversity in scene classification, this paper makes full
use of the contextual semantic relationships between the objects to describe the visual …