Convolutional neural network (CNN) has more and more applications in image recognition.
However, the structure of CNN is often determined after a performance comparison among …

Abstract Convolutional Neural Networks (CNNs) achieve state-of-the-art performance in
many recognition problems. However, CNN models are computation-intensive and require …

The writing style of the same writer varies from instance to instance in Arabic and English
handwritten digit recognition, making handwritten digit recognition challenging. Currently …

Convolutional Neural Networks (CNN) are on the forefront of accurate character recognition.
This paper explores CNNs at their maximum capacity by implementing the use of large …

When the elevation of targets is smaller than beamwidth, the coherent multi-path signals will
significantly degrade the direction of arrival (DOA) estimation accuracy of existing methods …

In this paper, we introduce a novel offline strategy for recognition of online handwritten
Devanagari characters entered in an unconstrained manner. Unlike the previous …

Large-scale convolutional neural network is a fundamental algorithmic building block in
many computer vision and artificial intelligence applications that follow the deep learning …

This paper presents a new topic of automatic recognition of bank note serial numbers, which
will not only facilitate the prevention of forgery crimes, but also have a positive impact on the …

The success of convolutional neural networks (CNNs) in the field of image recognition
suggests that local connectivity is one of the key issues to exploit the prior information of …

In recent years, many applications have been implemented in embedded systems and
mobile Internet of Things (IoT) devices that typically have constrained resources, smaller …