Antonio Guillén
Researcher / author (OpenAlex)
Facts
2 properties- Affiliation
- Hewlett Packard Enterpriseas of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
🔖 Identifiers · 2
- ORCID iD
- 0000-0003-3067-6469
- OpenAlex ID
- A5102853309as of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 8
AIM5LA: A Latency-Aware Deep Reinforcement Learning-Based Autonomous Intersection Management System for 5G Communication Networks,
A WiFi-based method to count and locate pedestrians in urban traffic scenarios,
Counting and locating people in outdoor environments: a comparative experimental study using WiFi-based passive methods,
Intelligent IoT systems for traffic management: A practical application,
Learning From Oracle Demonstrations—A New Approach to Develop Autonomous Intersection Management Control Algorithms Based on Multiagent Deep Reinforcement Learning,
Multi-Agent Deep Reinforcement Learning to Manage Connected Autonomous Vehicles at Tomorrow's Intersections,
RL-CAM: Visual Explanations for Convolutional Networks using Reinforcement Learning,
Robustness with Query-efficient Adversarial Attack using Reinforcement Learning
← Authored by 8
AIM5LA: A Latency-Aware Deep Reinforcement Learning-Based Autonomous Intersection Management System for 5G Communication Networks,
A WiFi-based method to count and locate pedestrians in urban traffic scenarios,
Counting and locating people in outdoor environments: a comparative experimental study using WiFi-based passive methods,
Intelligent IoT systems for traffic management: A practical application,
Learning From Oracle Demonstrations—A New Approach to Develop Autonomous Intersection Management Control Algorithms Based on Multiagent Deep Reinforcement Learning,
Multi-Agent Deep Reinforcement Learning to Manage Connected Autonomous Vehicles at Tomorrow's Intersections,
RL-CAM: Visual Explanations for Convolutional Networks using Reinforcement Learning,
Robustness with Query-efficient Adversarial Attack using Reinforcement Learning
Affiliated with 2
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Summary
Antonio Guillén is a human[1].