Background Artificial intelligence (AI) has served humanity in many applications since its
inception. Currently, it dominates the imaging field—in particular, image classification. The …

Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

Hodykin-Huxley 方程, 感知器模型与自适应滤波器, 再到六十年代的自组织映射网络,
神经认知机, 自适应共振网络, 许多神经计算模型都发展成为信号处理, 计算机视觉 …

Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …

We present a novel boundary-aware face alignment algorithm by utilising boundary lines as
the geometric structure of a human face to help facial landmark localisation. Unlike the …

Convolutional neural networks (CNNs) have been widely used in computer vision
community, significantly improving the state-of-the-art. In most of the available CNNs, the …

Over the past years, deep learning capabilities and the availability of large-scale training
datasets advanced rapidly, leading to breakthroughs in face recognition accuracy. However …

Air quality forecasting has been regarded as the key problem of air pollution early warning
and control management. In this article, we propose a novel deep learning model for air …

2)(西安交通大学人工智能与机器人研究所, 陕西西安, 710049) 摘要作为类脑计算领域的一个
重要研究成果, 深度卷积神经网络已经广泛应用到计算机视觉, 自然语言处理, 信息检索 …

This paper studies an approach to gait based human identification via similarity learning by
deep convolutional neural networks (CNNs). With a pretty small group of labeled multi-view …