With the advancement of Machine Learning, since its beginning and over the last years, a
special attention has been given to the Artificial Neural Network. As an inspiration from …

We propose a spiking neural network model that encodes information in the relative timing
of individual neuron spikes and performs classification using the first output neuron to spike …

The most prevalent cancer amongst women is woman breast cancer. Ultrasound imaging is
a widely employed method for identifying and diagnosing breast abnormalities. Computer …

This paper proposes a watermarking method for grayscale images, in which lifting wavelet
transform and singular value decomposition are exploited based on multi-objective artificial …

As the third generation of neural networks, spiking neural networks (SNNs) have gained
much attention recently because of their high energy efficiency on neuromorphic hardware …

Spiking neural networks with temporal coding schemes process information based on the
relative timing of neuronal spikes. In supervised learning tasks, temporal coding allows …

The subject of machine condition monitoring and fault diagnosis as a part of system
maintenance has gained a lot of interest due to the potential benefits to be learned from …

Traditional spiking learning algorithm aims to train neurons to spike at a specific time or on a
particular frequency, which requires precise time and frequency labels in the training …

The timing of individual neuronal spikes is essential for biological brains to make fast
responses to sensory stimuli. However, conventional artificial neural networks lack the …

There has been a lot of research on supervised learning in spiking neural network (SNN) for
a couple of decades to improve computational efficiency. However, evolutionary algorithm …