22 citations · 35 across the 14 of their papers we have counts for
3 papers · 1 filter
Improving Liver Disease Diagnosis with SNNDeep: A Custom Spiking Neural Network Using Diverse Learning Algorithms
Zofia Rudnicka, Janusz Szczepanski, Agnieszka Pregowska
Purpose: Spiking neural networks (SNNs) have recently gained attention as energy-efficient, biologically plausible alternatives to conventional deep learning models. Their applicat…
Learning Internal Biological Neuron Parameters and Complexity-Based Encoding for Improved Spiking Neural Networks Performance
Zofia Rudnicka, Janusz Szczepanski, Agnieszka Pregowska
This study proposes a novel learning paradigm for spiking neural networks (SNNs) that replaces the perceptron-inspired abstraction with biologically grounded neuron models, jointly…
Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection
Zofia Rudnicka, Januszcz Szczepanski, Agnieszka Pregowska
Spiking Neural Networks (SNNs) event-driven nature enables efficient encoding of spatial and temporal features, making them suitable for dynamic time-dependent data processing. Des…