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Years Active: 2013-2015
Title: Allen Yang Yang: Innovator in Motion Detection and Data Classification
Introduction
Allen Yang Yang is a prominent inventor based in Berkeley, CA. He has made significant contributions to the fields of motion detection and data classification. With a total of 2 patents, his work focuses on innovative methods that enhance the capabilities of wearable technology and data analysis.
Latest Patents
Yang's latest patents include a "System for detection of body motion" and "Recognition via high-dimensional data classification." The first patent outlines methods for classifying aggregated data in a distributed sensor system, particularly through a wearable motion sensor network. This system processes sensor data at individual nodes, reducing dimensionality and classifying actions based on training motion sequences. The base station then aggregates these measurements for global classification.
The second patent presents a method for recognizing high-dimensional data in the presence of occlusion. This involves receiving target data that includes an occlusion and is of an unknown class. By sampling training data files of distinct classes, the method identifies the class of the target data through linear superposition using l-minimization.
Career Highlights
Yang has worked at prestigious institutions such as the University of California and the University of Illinois. His experience in these academic environments has allowed him to develop and refine his innovative ideas in motion detection and data classification.
Collaborations
Throughout his career, Yang has collaborated with notable individuals, including Yi Ma and John Norbert Wright. These partnerships have contributed to the advancement of his research and the successful development of his patents.
Conclusion
Allen Yang Yang is a distinguished inventor whose work in motion detection and data classification has the potential to impact various technological fields. His innovative patents reflect a commitment to advancing wearable technology and data analysis methods.