Kiryat-Ono, Israel

Aharon Bar-Hillel


Average Co-Inventor Count = 2.7

ph-index = 2

Forward Citations = 12(Granted Patents)


Company Filing History:


Years Active: 2012-2019

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3 patents (USPTO):Explore Patents

Title: Aharon Bar-Hillel: Innovator in Gesture Recognition and Machine Learning

Introduction

Aharon Bar-Hillel is a notable inventor based in Kiryat-Ono, Israel. He has made significant contributions to the fields of gesture recognition and machine learning, holding a total of 3 patents. His work has implications for various technologies, enhancing user interaction through innovative methods.

Latest Patents

One of Bar-Hillel's latest patents focuses on gesture recognition. This method involves receiving a sequence of captured signal frames from a sensor to extract hand pose information. The process utilizes a trained predictor to analyze the received signal frames, allowing for the tracking of defined gestures through the computation of truth values related to hand poses. Another significant patent is centered on forward feature selection for support vector machines. This invention outlines a method for training a Support Vector Machine (SVM) using a subset of features, ranking them based on their quality, and selecting the most relevant features for improved performance.

Career Highlights

Throughout his career, Aharon Bar-Hillel has worked with prominent companies such as Intel Corporation and Microsoft Technology Licensing, LLC. His experience in these leading technology firms has contributed to his expertise and innovative capabilities in the field.

Collaborations

Bar-Hillel has collaborated with talented individuals, including Eyal Krupka and Kfir Karmon. These partnerships have likely fostered a creative environment that encourages the development of groundbreaking technologies.

Conclusion

Aharon Bar-Hillel's contributions to gesture recognition and machine learning exemplify his innovative spirit and dedication to advancing technology. His patents reflect a commitment to enhancing user interaction and improving machine learning methodologies.

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