SPATIO-TEMPORAL COOPERATIVE LEARNING FOR MULTI-SENSOR FUSION

Number of patents in Portfolio can not be more than 2000

United States of America

APP PUB NO 20250094535A1
SERIAL NO

18469424

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Abstract

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According to aspects described herein, a device can extract first features from frames of first sensor data and second features from frames of second sensor data (captured after the first sensor data). The device can obtain first weighted features based on the first features and second weighted features based on the second features. The device can aggregate the first weighted features to determine a first feature vector and the second weighted features to determine a second feature vector. The device can obtain a first transformed feature vector (based on transforming the first feature vector into a coordinate space) and a second transformed feature vector (based on transforming the second feature vector into the coordinate space). The device can aggregate first transformed weighted features (based on the first transformed feature vector) and second transformed weighted features (based on the second transformed feature vector) to determine a fused feature vector.

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Patent Owner(s)

Patent OwnerAddress
QUALCOMM INCORPORATED5775 MOREHOUSE DRIVE SAN DIEGO CA 92121-1714

International Classification(s)

Inventor(s)

Inventor Name Address # of filed Patents Total Citations
BHASKARAN, Vasudev San Diego, US 68 2359
NEHRUR, RAVI Arunkumar San Diego, US 2 0
PRIYADARSHI, Sweta San Diego, US 2 0
RAO, Shivansh San Diego, US 4 0
RAVI, KUMAR Varun San Diego, US 42 0
YOGAMANI, Senthil Kumar Headford, IE 51 7

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