Continuous computer vision (CV) tasks increasingly rely on convolutional neural networks
(CNN). However, CNNs have massive compute demands that far exceed the performance …

Point cloud analytics is poised to become a key workload on battery-powered embedded
and mobile platforms in a wide range of emerging application domains, such as …

Hardware support for deep convolutional neural networks (CNNs) is critical to advanced
computer vision in mobile and embedded devices. Current designs, however, accelerate …

An increasing number of edge systems have large computational demands, stringent
resource constraints, and end-to-end quality-driven goodness metrics. Architects have …

Over the past two decades, the use of low power Field Programmable Gate Arrays (FPGA)
for the acceleration of various vision systems mainly on embedded devices have become …

Quantization optimizes machine learning inference for resource constrained environments
by reducing the precision of its computation. In the extreme, even single-bit computations …

As we enter the era of domain-specific architectures, systems researchers must understand
the requirements of emerging application domains. Augmented and virtual reality (AR/VR) or …

Estimating depth from stereo vision cameras, ie," depth from stereo", is critical to emerging
intelligent applications deployed in energy-and performance-constrained devices, such as …

The emergence of virtual reality (VR) and augmented reality (AR) has revolutionized our
lives by enabling a 360° artificial sensory stimulation across diverse domains, including, but …

A 3-D reconstruction method and multicamera calibration using multiple artificial reference
markers have been used for precise volumetric surveillance of fast-flying objects. The …