Always-on TinyML perception tasks in IoT applications require very high
...
Exploiting sparsity is a key technique in accelerating quantized
convolu...
Structured matrices, such as those derived from Kronecker products (KP),...
Neural networks have gained importance as the machine learning models th...
Executing machine learning workloads locally on resource constrained
mic...
Convolutional neural network (CNN) inference on mobile devices demands
e...
Modern speech enhancement algorithms achieve remarkable noise suppressio...
Convolutional neural network (CNN) inference on mobile devices demands
e...
Lightweight architectural designs of Convolutional Neural Networks (CNNs...
The success of deep learning has brought forth a wave of interest in com...
Convolutional neural networks (CNNs) are now predominant components in a...
The vast majority of processors in the world are actually microcontrolle...
The computational demands of computer vision tasks based on state-of-the...