As a key technology of enabling Artificial Intelligence (AI) applications in 5G era, Deep
Neural Networks (DNNs) have quickly attracted widespread attention. However, it is …

深度学习算法和GPU 算力的不断进步, 正促进着人工智能技术在包括计算机视觉, 语音识别,
自然语言处理等领域得到广泛应用. 与此同时, 深度学习已经开始应用于以自动驾驶为代表的 …

Over the last decade, machine learning (ML) and deep learning (DL) algorithms have
significantly evolved and been employed in diverse applications, such as computer vision …

Deep neural networks (DNNs) have shown remarkable success in various machine-learning
(ML) tasks useful for many safety-critical, real-time embedded systems. The foremost design …

深度学习算法和 GPU 算力的不断进步, 正促进着人工智能技术在包括计算机视觉, 语音识别,
自然语言处理等领域得到广泛应用. 与此同时, 深度学习已经开始应用于以自动驾驶为代表的 …

The paper presents a real-time computing framework for intelligent real-time edge services,
on behalf of local embedded devices that are themselves unable to support extensive …

The paper discusses algorithmic priority inversion in mission-critical machine inference
pipelines used in modern neural-network-based cyber-physical applications, and develops …

Cutting-edge embedded system applications, such as self-driving cars and unmanned
drone software, are reliant on integrated CPU/GPU platforms for their DNNs-driven …

Today, an increasing number of Adaptive Deep Neural Networks (AdNNs) are being used
on resource-constrained embedded devices. We observe that, similar to traditional software …

Thanks to the recent advances in Deep Neural Networks (DNNs), DNN-based object
detection systems become highly accurate and widely used in real-time environments such …