Uusimaa, Finland

Daniel Herrera Castro

USPTO Granted Patents = 5 

Average Co-Inventor Count = 9.0

ph-index = 3

Forward Citations = 35(Granted Patents)


Company Filing History:


Years Active: 2021-2024

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5 patents (USPTO):Explore Patents

Title: Innovations of Daniel Herrera Castro

Introduction

Daniel Herrera Castro is a notable inventor based in Uusimaa, Finland. He has made significant contributions to the field of autonomous machine applications, holding a total of five patents. His work primarily focuses on enhancing the capabilities of machines to detect obstacles using advanced neural network technologies.

Latest Patents

One of his latest patents involves a method for distance to obstacle detection in autonomous machine applications. In this innovation, a deep neural network (DNN) is trained to accurately predict distances to objects and obstacles using image data alone. The DNN is trained with ground truth data generated from various depth predicting sensors, including RADAR, LIDAR, and SONAR sensors. Additionally, camera adaptation algorithms are employed to ensure the DNN can effectively utilize image data from cameras with varying parameters, such as different fields of view. A post-processing safety bounds operation is also integrated to ensure that the predictions made by the DNN remain within a safety-permissible range.

Career Highlights

Daniel currently works at Nvidia Corporation, a leading company in the field of graphics processing and artificial intelligence. His role involves developing innovative solutions that enhance the functionality of autonomous systems. His expertise in deep learning and machine vision has positioned him as a key player in advancing technology in this area.

Collaborations

Throughout his career, Daniel has collaborated with talented individuals such as Yilin Yang and Pekka Janis. These collaborations have fostered a creative environment that encourages the development of groundbreaking technologies.

Conclusion

Daniel Herrera Castro's contributions to the field of autonomous machine applications are noteworthy. His innovative patents and collaborative efforts continue to push the boundaries of technology, making significant strides in obstacle detection and machine learning.

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