Company Filing History:
Years Active: 2022-2025
Title: Manushree Gangwar: Innovator in Object Recognition Technology
Introduction
Manushree Gangwar is a prominent inventor based in San Francisco, CA. She has made significant contributions to the field of object recognition technology, holding a total of four patents. Her innovative work focuses on enhancing the capabilities of neural networks for object recognition.
Latest Patents
One of her latest patents is titled "Object recognition neural network training using multiple data sources." This invention involves methods, systems, and apparatus for training an object recognition neural network by utilizing various data sources. The process includes receiving training data that consists of multiple training images from different sources. Contrast equalization is applied to these images to generate modified images, which are then processed by the neural network to produce object recognition outputs. The parameters of the neural network are updated based on the determined loss from the outputs and ground-truth annotations.
Another notable patent is "Object recognition neural network for amodal center prediction." This invention describes methods and systems for processing images captured by a camera using an object recognition neural network. The network generates an object recognition output that includes data defining a predicted two-dimensional amodal center of the object, which is derived from a predicted three-dimensional center of the object.
Career Highlights
Manushree currently works at Magic Leap, Inc., where she continues to push the boundaries of technology in her field. Her work has garnered attention for its innovative approach to neural network training and object recognition.
Collaborations
She collaborates with talented individuals such as Siddharth Mahendran and Prateek Singhal, contributing to a dynamic work environment that fosters creativity and innovation.
Conclusion
Manushree Gangwar is a trailblazer in the realm of object recognition technology, with her patents reflecting her commitment to advancing the field. Her contributions are paving the way for future innovations in neural networks and object recognition systems.
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