Albert Thambiratnam

Title: Albert Thambiratnam: Innovator in Object Recognition Technology

Introduction

Albert Thambiratnam is a notable inventor based in Redmond, WA (US). He has made significant contributions to the field of object recognition technology, holding a total of 3 patents. His work focuses on enhancing the efficiency and accuracy of training data generation for machine learning applications.

Latest Patents

Thambiratnam's latest patents include innovative methods for automatically generating training data sets for object recognition. This patent outlines a method and apparatus for obtaining profile information of various objects. For each object, a group of initial images is collected based on the object's identity information. These images are then filtered to create a set of filtered images associated with the object. The final step involves generating training data pairs by labeling each filtered image with the corresponding identity information, which is then added to the training data set.

Another significant patent involves providing images with a privacy label. This method includes authenticating an entity, obtaining identity information based on the authentication, and acquiring images associated with the entity. Each image is then provided with a privacy label, ensuring that the entity's identity is protected.

Career Highlights

Albert Thambiratnam is currently employed at Microsoft Technology Licensing, LLC, where he continues to develop innovative solutions in the realm of object recognition. His expertise in this area has positioned him as a valuable asset to the company.

Collaborations

Thambiratnam has collaborated with notable colleagues, including Dehua Cui and Chenyang Cui, to further advance the field of object recognition technology.

Conclusion

Albert Thambiratnam's contributions to object recognition technology through his patents and work at Microsoft Technology Licensing, LLC highlight his role as an influential inventor in the tech industry. His innovative methods are paving the way for advancements in machine learning applications.