Deep learning approaches to anomaly detection (AD) have recently improved the state of
the art in detection performance on complex data sets, such as large collections of images or …

The vast proliferation of sensor devices and Internet of Things enables the applications of
sensor-based activity recognition. However, there exist substantial challenges that could …

Organizational decision-makers need to evaluate AI tools in light of increasing claims that
such tools outperform human experts. Yet, measuring the quality of knowledge work is …

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 models stand for a new learning paradigm in artificial intelligence (AI) and
machine learning. Recent breakthrough results in image analysis and speech recognition …

In recent years, there has been an exponential growth in the number of complex documents
and texts that require a deeper understanding of machine learning methods to be able to …

Features are the vital factor for image classification in the field of machine learning. The
advancement of deep convolutional neural network (CNN) shows the way for identification …

In recent years, deep learning has garnered tremendous success in a variety of application
domains. This new field of machine learning has been growing rapidly and has been …

Abstract Deep Convolutional Neural Network (CNN) is a special type of Neural Networks,
which has shown exemplary performance on several competitions related to Computer …

Over the past decades, a tremendous amount of research has been done on the use of
machine learning for speech processing applications, especially speech recognition …