Albert Gordo

Title: Albert Gordo: Innovator in Image Retrieval and Classification

Introduction

Albert Gordo is a prominent inventor based in Barcelona, Spain. He has made significant contributions to the fields of image retrieval and classification, holding a total of 3 patents. His work focuses on enhancing the accuracy and efficiency of image processing systems.

Latest Patents

One of Albert Gordo's latest patents is titled "Retrieval system and method leveraging category-level labels." This invention provides an instance-level retrieval method and system that embeds a representation of a query image in a multi-dimensional space using a learned projection. The projection is optimized using category-labeled training data to improve classification rates. This joint learning approach enhances the computation of similarity and distance between images, allowing for more accurate retrieval of similar instances from a database.

Another notable patent is "Document classification using multiple views." This invention describes a training system and method where a classifier is trained using a first 'cheap' view of training samples, while a second 'costly' view is not available during testing. An embedding function is learned to embed the first view into a common feature space, enabling the trained classifier to predict labels for test samples effectively.

Career Highlights

Albert Gordo is currently employed at Xerox Corporation, where he continues to innovate in the field of image processing. His work has had a significant impact on the development of advanced retrieval and classification systems.

Collaborations

Throughout his career, Albert has collaborated with notable colleagues, including Florent C Perronnin and Jose Antonio Rodriguez Serrano. These collaborations have contributed to the advancement of his research and the successful development of his patents.

Conclusion

Albert Gordo is a distinguished inventor whose work in image retrieval and classification has led to several impactful patents. His contributions continue to shape the future of image processing technologies.