The accuracies for many pattern recognition tasks have increased rapidly year by year,
achieving or even outperforming human performance. From the perspective of accuracy …

For more than 40 years, pattern recognition approaches are continuingly improving and
have been used in an increasing number of areas with great success. This book discloses …

Pattern recognition (PR) is the study of how machines can examine the environment, learn
to distinguish patterns of interest from their background, and make reliable and feasible …

The primary goal of pattern recognition is supervised or unsupervised classification. Among
the various frameworks in which pattern recognition has been traditionally formulated, the …

Deep learning has recently achieved great success in many visual recognition tasks.
However, the deep neural networks (DNNs) are often perceived as black-boxes, making …

Recent research in artificial intelligence and machine learning has largely emphasized
general-purpose learning and ever-larger training sets and more and more compute. In …

This letter proposes a new multiple linear regression model using regularized correntropy
for robust pattern recognition. First, we motivate the use of correntropy to improve the …

Featured Applications The main contribution of this work is to propose an inspection method
using image data generated at the actual manufacturing process. This proposed method can …

The primary goal of pattern recognition is supervised or unsupervised classification. Among
the various frameworks in which pattern recognition has been traditionally formulated, the …

Visual perception entails solving a wide set of tasks (eg, object detection, depth estimation,
etc). The predictions made for different tasks out of one image are not independent, and …