Abstract Design of hardware accelerators for neural network (NN) applications involves
walking a tight rope amidst the constraints of low-power, high accuracy and throughput …

In a world where security issues have been gaining growing importance, face recognition
systems have attracted increasing attention in multiple application areas, ranging from …

The biggest growth rate of network traffic in the coming years will be for smartphones and
Internet-connected devices, which relentless tend to perform increasingly demanding tasks …

Machine Learning over edge computing devices is levering up embedded and IoT
intelligence and is expected to grow even more. Today, Machine Learning applications are …

Limited resources and low computing power of embedded platform make it difficult to apply
neural network technology. To overcome this problem, a new neural network computing …

Object detection techniques that achieve state-of-the-art detection accuracy employ
convolutional neural networks, implemented to have lower latency in graphics processing …

With the increase in the non-linearity and complexity of the driving system's environment,
developing and optimizing related applications is becoming more crucial and remains an …

Artificial intelligence has evolved from the last years towards to large diversity of areas, such
as image recognition, audio recognition and data recommendation. To allow these areas to …

Cloud detection is an important step to avoid the interference of contaminated areas in the
remote sensing image. At present, the onboard cloud detection using deep learning is an …

Object detection techniques that achieve state-of-the-art detection accuracy employ
convolutional neural networks, implemented to have lower latency in graphics processing …