Hyperspectral imaging is an indispensable technology for many remote sensing
applications, yet expensive in terms of computing resources. It requires significant …

Using convolutional neural network (CNN) to identify plant diseases in-situ is a hot research
topic in smart agriculture. Due to the memory-intensive and compute-intensive …

Software and hardware development cycles have traditionally been quite distinct. Software
allows post-deployment patches, which leads to a rapid development cycle. In contrast …

In today's world, complexity is increasing and market demands new development tools for
Field Programmable Gate array (FPGA) in Convolution Neural Networks (CNN) applications …

This paper reports on the development of a resource-efficient FPGA-based neural network
regression model for potential applications in the future hardware muon trigger system of the …

Abstract Nowadays, Convolutional Neural Networks (CNN) have been widely adopted for
vision-based hand gesture recognition. Several existing CNN architectures designed for …

This study explores the implementation of lightweight binary classification algorithms on low-
cost Field-Programmable Gate Arrays (FPGAs) for medical image analysis. Recognizing the …

The mathematical model of 6-DoF dynamics is used in different applications. In general,
software-based solutions are utilized to implement the 6-DoF dynamic model. This paper …

In this paper, we evaluate the use of a trained Long Short-Term Memory (LSTM) network as
a surrogate for a Euler-Bernoulli beam model, and then we describe and characterize an …

The use of high level synthesis (HLS) tools is progressing in the industrial and academic
worlds as they have gained in maturity. In the last few years, they are commonly applied to …