Company Filing History:
Years Active: 2025
Title: Anton Mitrokhin: Innovator in Autonomous Driving Technologies
Introduction
Anton Mitrokhin is a prominent inventor based in Santa Clara, CA (US). He is known for his contributions to the field of autonomous driving technologies. His innovative work focuses on enhancing the perception capabilities of deep neural networks used in autonomous vehicles.
Latest Patents
Anton Mitrokhin holds 1 patent for his invention titled "Ground truth data generation for deep neural network perception in autonomous driving applications." This patent describes an annotation pipeline that produces 2D and/or 3D ground truth data for deep neural networks, particularly for autonomous or semi-autonomous vehicle perception networks. The process begins with capturing sensor data using various types of sensors, which are then synchronized to align frames representing a similar world state. The aligned frames are sampled and organized into annotation scenes for labeling. The annotation project is modular, allowing tasks to be encoded into a labeling tool that assigns tasks to labelers. During the annotation process, different types of sensor data are presented simultaneously, providing contextual information. Once all tasks are completed, the resulting ground truth data can be exported in various formats.
Career Highlights
Anton Mitrokhin is currently employed at Nvidia Corporation, a leading company in graphics processing and AI technologies. His work at Nvidia focuses on advancing the capabilities of autonomous driving systems through innovative data generation techniques.
Collaborations
Some of Anton's notable coworkers include Tilman Wekel and Joachim Pehserl, who contribute to the collaborative efforts in developing cutting-edge technologies in the field of autonomous driving.
Conclusion
Anton Mitrokhin's contributions to the field of autonomous driving through his innovative patent demonstrate his commitment to advancing technology in this critical area. His work at Nvidia Corporation continues to influence the future of autonomous vehicle perception systems.