With the success of deep learning in the field of computer vision, object recognition has
made important breakthroughs, and its recognition accuracy has been drastically improved …

In this work, we present a fully automated lung computed tomography (CT) cancer diagnosis
system, DeepLung. DeepLung consists of two components, nodule detection (identifying the …

Single image-based crowd counting has recently witnessed increased focus, but many
leading methods are far from optimal, especially in highly congested scenes. In this paper …

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 …

Scene recognition is currently one of the top-challenging research fields in computer vision.
This may be due to the ambiguity between classes: images of several scene classes may …

Scene recognition is an important computer vision task that has evolved from the study of the
biological visual system. Its applications range from video surveillance, autopilot systems, to …

Convolutional neural networks (CNNs) have made remarkable progress on scene
recognition, partially due to these recent large-scale scene datasets, such as the Places and …

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

As characterizing videos simultaneously from spatial and temporal cues has been shown
crucial for the video analysis, the combination of convolutional neural networks and …

Scene recognition is a kind of image recognition problems which is aimed at predicting the
category of the place at which the image is taken. In this paper, a new scene recognition …