In recent years, the landscape of computing paradigms has witnessed a gradual yet
remarkable shift from monolithic computing to distributed and decentralized paradigms such …

Video analytics with deep learning techniques has generated immense interest in academia
and industry, captivating minds with its transformative potential. Deep learning techniques …

Edge computing is a new paradigm enabling intelligent applications for the Internet of
Things (IoT) using mobile, low-cost IoT devices embedded with data analytics. Due to the …

In recent years, Deep Neural Network (DNN) has been increasingly adopted by a wide
range of time-critical applications running on edge platforms with heterogeneous …

Recent advances in deep neural networks have substantially improved the accuracy and
speed of various intelligent applications. Nevertheless, one obstacle is that DNN inference …

By leveraging the data sample diversity, the early-exit network recently emerges as a
prominent neural network architecture to accelerate the deep learning inference process …

Accurate navigation is of paramount importance to ensure flight safety and efficiency for
autonomous drones. Recent research starts to use Deep Neural Networks (DNN) to …

This work analyses the most relevant research conducted under the mobile cloud computing
paradigm to bring vision tasks supported by state-of-the-art deep convolutional neural …

Accurate navigation is of paramount importance to ensure flight safety and efficiency for
autonomous drones. Recent research starts to use Deep Neural Networks (DNN) to …

Achieving efficient execution of machine learning models has attracted significant attention
recently. To generate tensor programs efficiently, a key component of DNN compilers is the …