Machine learning with a snapshot of data: Spiking neural network 'predicts' reinforcement histories of pigeons' choice behavior

A Plessas, JI Espinosa‐Ramos, D Parry… - Journal of the …, 2022 - Wiley Online Library
An accumulated body of choice research has demonstrated that choice behavior can be
understood within the context of its history of reinforcement by measuring response patterns …

Novel Spiking Neural Network Model for Gear Fault Diagnosis

YH Ali, FYH Ahmed, AM Abdelrhman… - … on Emerging Smart …, 2022 - ieeexplore.ieee.org
Gearbox is an important component in machine system. Hence, it is important to predict and
maintain the performance of the gear system, since any unpredictable failure in this system …

STNet: A novel spiking neural network combining its own time signal with the spatial signal of an artificial neural network

F Liu, W Tao, J Yang, W Wu, J Wang - Frontiers in Neuroscience, 2023 - frontiersin.org
Introduction This article proposes a novel hybrid network that combines the temporal signal
of a spiking neural network (SNN) with the spatial signal of an artificial neural network …

Digit Recognition in Spiking Neural Networks using Wavelet Transform

H Aghabarar, K Kiani… - Journal of AI and Data …, 2023 - jad.shahroodut.ac.ir
Nowadays, given the rapid progress in pattern recognition, new ideas such as theoretical
mathematics can be exploited to improve the efficiency of these tasks. In this paper, the …

Self-Supervised Contrastive Learning In Spiking Neural Networks

Y Bahariasl, SR Kheradpisheh - 2024 13th Iranian/3rd …, 2024 - ieeexplore.ieee.org
Spiking neural networks (SNNs), inspired by the biological neural processing of the brain,
are vastly growing due to their higher potential to handle spatiotemporal patterns with lower …

Deep Learning Techniques and Drug Release

S Singh, S Rawat, R Malviya, S Sundram… - … industry 4.0: Future …, 2023 - taylorfrancis.com
Pharmaceutical formulation development appears to be heavily reliant on the labor-
intensive, time-consuming, and expensive traditional trial-and-error method based on the …

Hierarchical Temporal Memory for Anomaly Detection in Videos

V Monakhov - 2022 - duo.uio.no
The use of video anomaly detection systems has gained traction for the past few years. The
current approaches use deep learning for performing anomaly detection in videos, but this …