This inventor holds 1 USPTO granted patent. Top assignees: ETH Zurich, Toyota Jidosha Kabushiki Kaisha. Active years: 2016.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:


Years Active: 2016
Title: Juergen Gall: Innovator in Object Recognition Technology
Introduction
Juergen Gall is a prominent inventor based in Zurich, Switzerland. He is known for his contributions to the field of object recognition technology. His innovative approach has led to the development of a unique patent that enhances the capabilities of image recognition systems.
Latest Patents
Juergen Gall holds a patent for an object recognition device. This device features a learning unit that generates a function table indicating the relationship between class numbers and position information of an object. It also calculates a sharing matrix that indicates the commonality of feature amounts between classes. The device creates a tree diagram clustering classes with similar feature amounts and calculates the weight of each node in the tree diagram for each small area image pattern. The recognition processing unit compares image data captured by a camera with a code book, selects the closest small area image pattern, and extracts the class related to the node with the smallest weight. This process allows for effective object recognition.
Career Highlights
Throughout his career, Juergen Gall has worked with notable companies, including Toyota Motor Corporation and ETH Zurich (Eidgenössische Technische Hochschule Zurich). His experience in these organizations has contributed significantly to his expertise in the field of object recognition.
Collaborations
Juergen Gall has collaborated with esteemed colleagues such as Nima Razavi and Luc Van Gool. Their joint efforts have further advanced the research and development of innovative technologies in object recognition.
Conclusion
Juergen Gall's work in object recognition technology exemplifies the impact of innovation in enhancing machine learning capabilities. His patent and collaborations reflect his commitment to advancing this field.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile