Most methods for time series classification that attain state-of-the-art accuracy have high
computational complexity, requiring significant training time even for smaller datasets, and …

“Any AI smart enough to pass a Turing test is smart enough to know to fail it.”–*** Ian
McDonald Neural networks were developed to simulate the human nervous system for …

Machine learning techniques based on neural networks are achieving remarkable results in
a wide variety of domains. Often, the training of models requires large, representative …

In the era of the so called 4th industrial revolution, the Factory of the Future and the Industrial
Internet of Things, the industrial mechanical systems become continuously more intelligent …

An introduction to a broad range of topics in deep learning, covering mathematical and
conceptual background, deep learning techniques used in industry, and research …

Abstract In 2007, Labeled Faces in the Wild was released in an effort to spur research in
face recognition, specifically for the problem of face verification with unconstrained images …

Inventors have long dreamed of creating machines that think. Ancient Greek myths tell of
intelligent objects, such as animated statues of human beings and tables that arrive full of …

Feature extraction is vital for face recognition. In this paper, we focus on the general feature
extraction framework for robust face recognition. We collect about 300 papers regarding face …

Many computer vision algorithms depend on configuration settings that are typically hand-
tuned in the course of evaluating the algorithm for a particular data set. While such …

Biometrics systems have significantly improved person identification and authentication,
playing an important role in personal, national, and global security. However, these systems …