Toronto, Canada

Evgeny Nuger

This inventor holds 1 USPTO granted patent and 1 EPO patent. Top assignee: Hitachi Rail Gts Canada Inc.. Active years: 2025.


% Patents Active = 100.0


Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Evgeny Nuger: Innovator in Machine-Learned Object Detection

Introduction

Evgeny Nuger is a notable inventor based in Toronto, Canada. He has made significant contributions to the field of machine learning and object detection. His innovative work has led to the development of a unique patent that enhances the capabilities of vehicle navigation systems.

Latest Patents

Evgeny Nuger holds a patent for a "Machine-learned explainable object detection system and method." This invention involves a method of detecting a way-side object by receiving data frames from sensors mounted on a vehicle. The system processes position data corresponding to the vehicle's location and retrieves object-of-interest data from a database. By analyzing the sensor data frames and the object-of-interest data, the system determines a region-of-interest. It then employs machine-learned object detection to identify the first object-of-interest and utilizes computer vision methods to detect features of the expected object. The explained object-of-interest data is subsequently output to the vehicle's navigation system.

Career Highlights

Evgeny Nuger is currently employed at Hitachi Rail GTS Canada Inc. His work focuses on integrating advanced technologies into transportation systems. With a strong background in machine learning, he has been instrumental in developing innovative solutions that improve safety and efficiency in rail systems.

Collaborations

Evgeny collaborates with talented professionals in his field, including Veronica Marin and Jaewook Jung. Their combined expertise contributes to the success of their projects and the advancement of technology in transportation.

Conclusion

Evgeny Nuger is a pioneering inventor whose work in machine-learned object detection is shaping the future of vehicle navigation systems. His contributions are vital to enhancing safety and efficiency in transportation.

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