Convolutional neural network (CNN)-based object detection has been widely employed in
various applications such as autonomous driving and intelligent video surveillance …

Many algorithms feature an iterative loop that converges to the result of interest. The
numerical operations in such algorithms are generally implemented using finite-precision …

Considering the widespread diffusion of mobile applications in many aspects of our life, one
of the most required developer's skill is related to mobile applications development, with …

In our recent work on iterative computation in hardware, we showed that arbitrary-precision
solvers can perform more favorably than their traditional arithmetic equivalents when the …

Quasi-Newton (QN) method is one of the most effective Neural Network (NN) training
methods. However, QN training often needs long time especially when the NN architecture …

Quasi-Newton (QN) methods are now widely used for NN training due to their high
effectiveness. In practice, the iterative process of the QN methods implemented in software is …

We recently proposed the first hardware architecture enabling the iterative solution of
systems of linear equations to accuracies limited only by the amount of available memory …