Gdansk, Poland

Maciej Budys


Average Co-Inventor Count = 8.0

ph-index = 1

Forward Citations = 3(Granted Patents)


Company Filing History:


Years Active: 2023-2025

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2 patents (USPTO):Explore Patents

Title: Maciej Budys: Innovator in Traffic Violation Validation Systems

Introduction

Maciej Budys is a notable inventor based in Gdansk, Poland. He has made significant contributions to the field of traffic violation validation through his innovative patents. With a total of two patents to his name, Budys is recognized for his work in developing systems that enhance the accuracy and efficiency of traffic law enforcement.

Latest Patents

Budys' latest patents focus on systems and methods for automatically validating evidence of traffic violations using automatically detected context features. These patents disclose methods and systems that involve receiving an evidence package comprising video frames showing a vehicle involved in a potential traffic violation. The video frames are processed through one or more deep learning models to obtain a plurality of classification results. The method further includes generating a score based on the classification results and evaluating this score against one or more thresholds. This evaluation determines whether the evidence package is automatically approved, automatically rejected, or requires further review.

Career Highlights

Throughout his career, Maciej Budys has worked with companies such as Hayden AI Technologies, Inc. and Hayden Al Technologies, Inc. His experience in these organizations has contributed to his expertise in developing advanced technological solutions for traffic management.

Collaborations

Budys has collaborated with talented individuals in his field, including Wiktor Muron and Andrei Liaukovich. These collaborations have likely enriched his work and led to innovative advancements in traffic violation validation systems.

Conclusion

Maciej Budys stands out as an inventor dedicated to improving traffic law enforcement through technology. His patents reflect a commitment to innovation and the application of deep learning in real-world scenarios.

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