Jong Tae Ahn

20200117955, Apr 16, 2020

Oct 11, 2018

16/158097

- Espoo, FI
Jong Hoon Ahn - Bound Brook NJ, US
Xiaoyang Wang - New Providence NJ, US

G06K 9/62
G06K 9/46

The present disclosure is directed to a method to generate a recovered image from a compressive measurement vector. The method uses a trained machine learning (ML) model, generated from a decomposed sensing matrix and a compressive measurement labeled pair, to generate a feature vector that has a dimensional value less than that for the recovered image. The feature vector can be linearly transformed into the recovered image. Also disclosed is a system operable to execute a process to train a ML model using a decomposed sensing matrix, a training image, and a compressive measurement vector representing the training image. A system is also disclosed that is operable to utilize a trained ML model and a decomposed sensing matrix to estimate a recovered image represented by a compressive measurement vector.