SYSTEM AND METHOD FOR THE FUSION OF BOTTOM-UP WHOLE-IMAGE FEATURES AND TOP-DOWN ENTTIY CLASSIFICATION FOR ACCURATE IMAGE/VIDEO SCENE CLASSIFICATION

Described is a system and method for accurate image and/or video scene classification. More specifically, described is a system that makes use of a specialized convolutional-neural network (hereafter CNN) based technique for the fusion of bottom-up whole-image features and top-down entity classifica...

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Bibliographic Details
Main Authors Chen, Yang, Uhlenbrock, Ryan M, Khosla, Deepak, Monterroza, Fredy
Format Patent
LanguageEnglish
Published 03.01.2019
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
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Summary:Described is a system and method for accurate image and/or video scene classification. More specifically, described is a system that makes use of a specialized convolutional-neural network (hereafter CNN) based technique for the fusion of bottom-up whole-image features and top-down entity classification. When the two parallel and independent processing paths are fused, the system provides an accurate classification of the scene as depicted in the image or video.
Bibliography:Application Number: US201715427597