Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices,
and models that contrast the pervasive von Neumann computer architecture. This …

The last 50 years has witnessed considerable research in the area of neural networks
resulting in a range of architectures, learning algorithms and demonstrative applications. A …

This paper presents a novel hardware implementation of Artificial Neural Networks (ANNs)
for modeling of the Pehlivan–Uyaroglu Chaotic System (PUCS) on Field Programmable …

Low-level computer vision algorithms have extreme computational requirements. In this
work, we compare two real-time architectures developed using FPGA and GPU devices for …

The proposed work presents a highly parallel architecture for motion estimation. Our system
implements the well-known Lucas and Kanade algorithm with the multi-scale extension for …

This paper proposes a serial hardware architecture of a multilayer perceptron (MLP) neural
network for real-time wheezing detection in respiratory sounds. As an established …

Abstract Multi-label Text Classification (MTC) is a challenging task in Natural Language
Processing (NLP). The goal of the MTC task is to label a document with a set of labels. By …

Neuromorphic computing has become an attractive candidate for emerging computing
platforms. It requires an architectural perspective, meaning the topology or hyperparameters …

Artificial neural network (ANN) is widely used in modern engineering applications. The
decision on the number of layers and the number of nodes per layer in the ANN or the …

In this paper, we propose a hardware-based architecture for automatic blue whale calls
classification based on short-time Fourier transform and multilayer perceptron neural …