Company Filing History:
Years Active: 2025
Title: Ines Ugalde Diaz: Innovator in Object Detection and Classification
Introduction
Ines Ugalde Diaz is a prominent inventor based in Redwood City, CA (US). She has made significant contributions to the field of computer science, particularly in the area of object detection and classification using deep learning techniques. Her innovative approach has the potential to enhance various applications in artificial intelligence and machine learning.
Latest Patents
Ines holds a patent for a groundbreaking method titled "Synthetic dataset creation for object detection and classification with deep learning." This computer-implemented method involves building an object detection module that utilizes mesh representations of objects belonging to specified classes. The process includes rendering images through a physics-based simulator, capturing simulated environments with multiple object classes. Each rendered image is generated by randomizing parameters, including environmental and sensor-based factors, to create a diverse range of training data. The resulting synthetic training dataset is used to train a deep learning model, enabling it to identify object classes from real-world images.
Career Highlights
Ines is currently employed at Siemens Corporation, where she continues to push the boundaries of innovation in her field. Her work at Siemens allows her to collaborate with other talented professionals and contribute to cutting-edge projects that leverage her expertise in deep learning and object detection.
Collaborations
Ines has worked alongside notable colleagues such as Eugen Solowjow and Yash Shahapurkar. These collaborations have fostered a dynamic environment for innovation and have led to the development of advanced technologies in their respective fields.
Conclusion
Ines Ugalde Diaz is a trailblazer in the realm of object detection and classification, with her patent and work at Siemens Corporation showcasing her commitment to advancing technology. Her contributions are paving the way for future innovations in artificial intelligence and machine learning.