The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Aug. 20, 2019
Filed:
May. 19, 2018
Gyrfalcon Technology Inc., Milpitas, CA (US);
Lin Yang, Milpitas, CA (US);
Patrick Z. Dong, San Jose, CA (US);
Charles Jin Young, Fremont, CA (US);
Jason Z. Dong, San Jose, CA (US);
Wenhan Zhang, Mississauga, CA;
Baohua Sun, Fremont, CA (US);
Gyrfalcon Technology Inc., Milpitas, CA (US);
Abstract
A deep learning object detection and recognition system contains a number of cellular neural networks (CNN) based integrated circuits (ICs) operatively coupling together via the network bus. The system is configured for detecting and then recognizing one or more objects out of a two-dimensional (2-D) imagery data. The 2-D imagery data is divided into N set of distinct sub-regions in accordance with respective N partition schemes. CNN based ICs are dynamically allocated for extracting features out of each sub-region for detecting and then recognizing an object potentially contained therein. Any two of the N sets of sub-regions overlap each other. N is a positive integer. Object detection is achieved with a two-category classification using a deep learning model based on approximated fully-connected layers, while object recognition is performed using a local database storing feature vectors of known objects.