Deep Neural Networks (DNNs) have been widely used in various artificial intelligence (AI)
applications due to their overwhelming performance. Furthermore, recently, several …

Softmax is a common and complex activation function in Deep Neural Networks (DNN).
However, it is a challenge to apply it efficiently in DNN training hardware accelerator …

On-chip training improves model accuracy on personalised user data and preserves privacy.
This work proposes REACT, an AI accelerator for wearables that has heterogeneous cores …

Deep learning is now widely used in many fields, including engineering and medicine. CNN
is the most widely used deep learning model due to its high accuracy in image recognition …

Sending local data to cloud servers is vulnerable to user privacy, and its long update
latency. Meanwhile, the state-of-the-art stereo matching method is still computation …

The emergence of data parallel architectures have enabled new opportunities to address
the power limitations and scalability of multi-core processors, allowing new ways to exploit …

To achieve higher accuracy on local devices, the necessity of retraining a DNN model on
edge increases. This paper proposes a sparsity and mixed-precision aware edge learning …