Renningen, Germany

Florian Drews

USPTO Granted Patents = 3 

 

Average Co-Inventor Count = 9.9

ph-index = 1


Company Filing History:


Years Active: 2022-2025

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3 patents (USPTO):Explore Patents

Title: Florian Drews: Innovator in Sensor Technology

Introduction

Florian Drews is a notable inventor based in Renningen, Germany. He has made significant contributions to the field of sensor technology, holding a total of 3 patents. His work focuses on enhancing the capabilities of sensor systems through innovative methods and machine learning techniques.

Latest Patents

Florian's latest patents include a "Method for training and operating movement estimation of objects." This invention involves the extraction of movement information from sensor data by providing a time series of frames and object boundary boxes. The method utilizes a trainable machine learning model to predict object boundary boxes, optimizing parameters based on deviations from predicted outcomes.

Another significant patent is the "Method for monitoring surroundings of a first sensor system." This method generates a temporal sequence of data to improve monitoring capabilities. It employs a trained neural network to identify subregions of the surroundings, enhancing the effectiveness of a second sensor system through generated control signals.

Career Highlights

Florian Drews is currently employed at Robert Bosch GmbH, a leading company in engineering and technology. His role involves developing advanced sensor technologies that contribute to various applications in the industry. His innovative approaches have positioned him as a key figure in the field.

Collaborations

Florian has collaborated with talented coworkers, including Claudius Glaeser and Lars Rosenbaum. Their combined expertise fosters a creative environment that drives innovation in sensor technology.

Conclusion

Florian Drews exemplifies the spirit of innovation in sensor technology through his patents and contributions at Robert Bosch GmbH. His work continues to influence advancements in the field, showcasing the importance of integrating machine learning with sensor systems.

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