DEEP LEARNING ARCHITECTURE FOR AUTOMATED IMAGE FEATURE EXTRACTION

Systems and techniques for facilitating a deep learning architecture for automated image feature extraction are presented. In one example, a system includes a machine learning component. The machine learning component generates learned imaging output regarding imaging data based on a convolutional n...

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Bibliographic Details
Main Authors Zhang, Min, Avinash, Gopal Biligeri
Format Patent
LanguageEnglish
Published 25.04.2019
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
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Summary:Systems and techniques for facilitating a deep learning architecture for automated image feature extraction are presented. In one example, a system includes a machine learning component. The machine learning component generates learned imaging output regarding imaging data based on a convolutional neural network that receives the imaging data. The machine learning component also performs a plurality of sequential and/or parallel downsampling and upsampling of the imaging data associated with convolutional layers of the convolutional neural network.
Bibliography:Application Number: US201715854971