While diffusion models demonstrate a remarkable capability for generatin...
In this paper, we describe and analyze an island-based random dynamic vo...
Logic locking has become a promising approach to provide hardware securi...
Spiking Neural networks (SNN) have emerged as an attractive spatio-tempo...
Spiking Neural Networks (SNNs) have emerged as an attractive spatio-temp...
In order to deploy current computer vision (CV) models on
resource-const...
Hyperspectral cameras generate a large amount of data due to the presenc...
Sequential logic locking has been studied over the last decade as a meth...
Spiking neural networks (SNNs), that operate via binary spikes distribut...
The SAT attack has shown to be efficient against most combinational logi...
Scan chains provide increased controllability and observability for test...
This paper presents a dynamic network rewiring (DNR) method to generate
...
Seminal work by Cortadella, Kondratyev, Lavagno, and Sotiriou includes a...
We present Deep-n-Cheap – an open-source AutoML framework to search for ...
Single flux quantum (SFQ) circuits are an attractive beyond-CMOS technol...
The high energy cost of processing deep convolutional neural networks im...
The risk of soft errors due to radiation continues to be a significant
c...
The high computational complexity associated with training deep neural
n...
The high demand for computational and storage resources severely impede ...
The high demand for computational and storage resources severely impede ...
Latch-based designs have many benefits over their flip-flop based
counte...
Neural networks have proven to be extremely powerful tools for modern
ar...
We present an algorithm to generate synthetic datasets of tunable diffic...
We demonstrate an FPGA implementation of a parallel and reconfigurable
a...
We propose a novel way of reducing the number of parameters in the
stora...
We propose a reconfigurable hardware architecture for deep neural networ...