Company Filing History:
Years Active: 2021-2025
Title: Fabian Timm: Innovator in Sensor Technology
Introduction
Fabian Timm is a notable inventor based in Renningen, Germany. He has made significant contributions to the field of sensor technology, holding a total of 4 patents. His work focuses on enhancing the capabilities of sensor systems through innovative methods.
Latest Patents
One of Timm's latest patents is a method for training and operating movement estimation of objects. This method involves providing a time series of frames of sensor data recorded by physical observation of an object. It also includes supplying the object boundary box at a specific time, along with a history of sensor data and object boundary boxes. This information is used to train a machine learning model that predicts future object boundary boxes, optimizing the model's parameters based on deviations from actual data.
Another significant patent is a method for monitoring the surroundings of a first sensor system. This method generates a temporal sequence of data from the first sensor system and creates an input tensor for a trained neural network. The neural network identifies subregions of the surroundings to improve monitoring with a second sensor system, generating control signals to enhance overall surveillance.
Career Highlights
Fabian Timm works at Robert Bosch GmbH, a leading company in engineering and technology. His role involves developing advanced sensor technologies that contribute to various applications in automation and monitoring systems. His innovative approaches have positioned him as a key figure in the field.
Collaborations
Timm collaborates with talented individuals such as Sebastian Muenzner and Jasmin Ebert. Their teamwork fosters a creative environment that drives innovation and enhances the development of new technologies.
Conclusion
Fabian Timm's contributions to sensor technology through his patents and work at Robert Bosch GmbH highlight his role as an influential inventor. His innovative methods are paving the way for advancements in monitoring systems and movement estimation.