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 …

Abstract Machine Learning (ML) and Deep Learning (DL) have achieved high success in
many textual, auditory, medical imaging, and visual recognition patterns. Concerning the …

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

Image pattern recognition in the field of big data has gained increasing importance and
attention from researchers and practitioners in many domains of science and technology …

Automatic (machine) recognition, description, classification, and groupings of patterns are
important problems in a variety of engineering and scientific disciplines such as biology …

In research of pattern recognition, we always want to achieve the correct classification rate
according to the characteristics required. Feature extraction greatly affects the design and …

In the current age of the Fourth Industrial Revolution (4 IR or Industry 4.0), the digital world
has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data …

Recent technological advancements in data acquisition tools allowed life scientists to
acquire multimodal data from different biological application domains. Categorized in three …

The two-volume set CCIS 483 and CCIS 484 constitutes the refereed proceedings of the 6th
Chinese Conference on Pattern Recognition, CCPR 2014, held in Changsha, China, in …

Pattern recognition has become more and more popular and important to us since 1960's
and it induces attractive attention coming from a wider areas. In this paper Pattern …