Daniel Casanueva-Morato

Orcid: 0000-0002-7676-1629

According to our database1, Daniel Casanueva-Morato authored at least 11 papers between 2022 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
Competitive cost-effective memory access predictor through short-term online SVM and dynamic vocabularies.
Future Gener. Comput. Syst., 2025

2024
Bio-inspired computational memory model of the Hippocampus: An approach to a neuromorphic spike-based Content-Addressable Memory.
Neural Networks, 2024

A Low-Cost Real-Time Spiking System for Obstacle Detection based on Ultrasonic Sensors and Rate Coding.
CoRR, 2024

Integrating a hippocampus memory model into a neuromorphic robotic-arm for trajectory navigation.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

2023
Bioinspired Spike-Based Hippocampus and Posterior Parietal Cortex Models for Robot Navigation and Environment Pseudomapping.
Adv. Intell. Syst., November, 2023

Construction of a Spike-Based Memory Using Neural-Like Logic Gates Based on Spiking Neural Networks on SpiNNaker.
IEEE Trans. Emerg. Top. Comput., 2023

Bio-inspired spike-based Hippocampus and Posterior Parietal Cortex models for robot navigation and environment pseudo-mapping.
CoRR, 2023

Live Demonstration: Bio-inspired implementation of a sparse-learning spike-based hippocampus memory model.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2023

2022
A bio-inspired implementation of a sparse-learning spike-based hippocampus memory model.
CoRR, 2022

Spike-based computational models of bio-inspired memories in the hippocampal CA3 region on SpiNNaker.
Proceedings of the International Joint Conference on Neural Networks, 2022

Spike-based building blocks for performing logic operations using Spiking Neural Networks on SpiNNaker.
Proceedings of the International Joint Conference on Neural Networks, 2022


  Loading...