Francisca Rosique

Publications

• A graphical modeling language for home automation
• Applying Vision-Based Pose Estimation in a Telerehabilitation Application
• U-DSL: a Domain Specific Language for Ubiquitous Systems
• Personal Assistance and Monitoring Devices Applications
• Is the Rural Population Caught in the Whirlwind of the Digital Divide?
• End-to-End Deep Neural Network Architectures for Speed and Steering Wheel Angle Prediction in Autonomous Driving
• A framework for developing component-based applications with temporal analysis capabilities
• An implementation framework for component-based applications with real-time constraints: Extensions for achieving component distribution
• A tool for facilitating the teaching of smart home applications
• A Component-based meta-model and framework in the model driven toolchain C-Forge
• Transforming and tracing reused requirements models to home automation models
• Traceability support for MDE development of Home Automation systems
• Lessons learned in applying MDE to the development of Home Automation systems
• Introducing safety requirements traceability support in model-driven development of robotic applications
• A framework for developing home automation systems: From requirements to code
• Habitation: A domain-specific language for home automation
• An augmented reality mirror exergame using 2D pose estimation
• Adapting a Component-based Model Approach to SOA: A robotic experience
• Towards a unified platform for agent-based cloud robotics
• A systematic review of perception system and simulators for autonomous vehicles research
• Modeling and executing component-based applications in C-Forge
• Using Artificial Vision for Measuring the Range of Motion
• Autonomous Vehicle Dataset with Real Multi-Driver Scenes and Biometric Data
• 7. End-to-end architectures
• EdgeNet: An End-to-End Deep Neural Network pretrained with Synthetic Data for a Real-World Autonomous Driving Application
• Situación y retos del aislamiento digital en las zonas rurales españolas
• EdgeNet: An End-to-End Deep Neural Network Pretrained with Synthetic Data for a Real-World Autonomous Driving Application
• Conditional generative adversarial network for segmentation and image reconstruction of grape berries in variable illumination conditions