Embedded intelligence (EI) is an emerging research field and has the objective to
incorporate machine learning algorithms and intelligent decision-making capabilities into …

Electrocardiography (ECG) has been used as a diagnostic tool for various heart diseases. It
is most effective in detecting myocardial infarction and fatal arrhythmias. This work proposes …

Convolutional neural networks (CNNs) based deep learning algorithms require high data
flow and computational intensity. For real-time industrial applications, they need to …

Field Programmable Gate Array (FPGA) has become an efficient accelerator for
convolutional neural network (CNN) inference due to its high performance and flexibility. To …

Convolutional Neural Networks (CNN) continue to dominate research in the area of
hardware acceleration using Field Programmable Gate Arrays (FPGA), proving its …

Adversarial examples have emerged as a significant threat to machine learning algorithms,
especially to the convolutional neural networks (CNNs). In this paper, we propose two …

Leveraging deep convolutional neural networks (DCNNs) for various application areas has
become a recent inclination of many machine learning practitioners due to their impressive …

The hardware acceleration of Deep Neural Networks (DNN) is a highly effective and viable
solution for running them on mobile devices. The power of DNNs is now available at the …

Standard convolutional neural networks (CNNs) have large amounts of data redundancy,
and the same accuracy can be obtained even in lower bit weights instead of floating-point …

The field programmable gate array (FPGA) is used to build an artificial neural network in
hardware. Architecture for a digital system is devised to execute a feed-forward multilayer …