Successful integration of deep neural networks (DNNs) or deep learning (DL) has resulted
in breakthroughs in many areas. However, deploying these highly accurate models for data …

The breakthrough of deep learning has started a technological revolution in various areas
such as object identification, image/video recognition and semantic segmentation. Neural …

Low-precision arithmetic operations to accelerate deep-learning applications on field-
programmable gate arrays (FPGAs) have been studied extensively, because they offer the …

Video super-resolution (VSR) technology excels in reconstructing low-quality video,
avoiding unpleasant blur effect caused by interpolation-based algorithms. However, vast …

As a typical artificial intelligence algorithm, the convolutional neural network (CNN) is widely
used in the Internet of Things (IoT) system. In order to improve the computing ability of an IoT …

In this article, we analyze algorithmic ways to reduce the arithmetic complexity of calculating
quaternion-valued linear convolution and also synthesize a new algorithm for calculating …

With the proliferation of low-cost sensors and the Internet-of-Things (IoT), the rate of
producing data far exceeds the compute and storage capabilities of today's infrastructure …

With the proliferation of low-cost sensors and the Internet of Things, the rate of producing
data far exceeds the compute and storage capabilities of today's infrastructure. Much of this …

Three-dimensional (3D) deconvolution is widely used in many computer vision applications.
However, most previous works have only focused on accelerating two-dimensional (2D) …

Convolutional neural networks (CNNs) are widely adopted in safety-critical systems,
including space applications and autonomous vehicles. Field-programmable gate arrays …