This inventor holds 1 USPTO granted patent. Top assignees: Siemens Aktiengesellschaft, University System of Maryland. Active years: 2016.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:


Years Active: 2016
Title: Sameh Khamis: Innovator in Automated Person Re-Identification
Introduction
Sameh Khamis is a notable inventor based in College Park, MD (US). He has made significant contributions to the field of automated person re-identification. His innovative approach combines machine learning with semantic understanding to enhance the accuracy of identifying individuals in various contexts.
Latest Patents
Sameh Khamis holds a patent for a groundbreaking invention titled "Machine-learnt person re-identification." This patent focuses on automating the process of person re-identification by considering various attributes of individuals. The method involves solving for similarities across multiple attributes and identities, capturing discriminative interactions effectively. Notably, the invention utilizes semantic color names instead of traditional color histograms, mapping probability distributions to these terms. This approach allows for a more nuanced understanding of color and other descriptors, which are combined into a comprehensive similarity score.
Career Highlights
Throughout his career, Sameh Khamis has worked with prominent organizations, including Siemens Aktiengesellschaft and the University System of Maryland. His experience in these institutions has allowed him to refine his skills and contribute to significant advancements in technology.
Collaborations
Sameh has collaborated with talented individuals such as Vinay Damodar Shet and Cheng-Hao Kuo. These partnerships have fostered innovation and have been instrumental in the development of his patented technologies.
Conclusion
Sameh Khamis is a distinguished inventor whose work in automated person re-identification showcases the potential of machine learning in enhancing identification processes. His contributions continue to influence the field and pave the way for future innovations.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile