US 2019/0095764 A1 · METHOD AND SYSTEM FOR DETERMINING OBJECTS DEPICTED IN IMAGES

Abstract

Techniques are disclosed for identifying objects in images. In one embodiment, transfer learning is employed to build new classifiers on top of pre-trained machine learning models, such as pre-trained convolutional neural networks (CNNs), by re-training classification layers of the pre-trained machine learning models using new training data while keeping feature detection layers of the pre-trained machine learning models fixed. Subsequently, the re-trained machine learning models may take as input images depicting regions of interest extracted from larger images using a sliding window, a saliency map, an image disparity map, and/or a region of interest detection technique, and output classifications of objects in the input images. In addition, a meta model may be learned that aggregates outputs of the re-trained machine learning models for robustness.

Claims20

Dependent claims

A computer-implemented method for identifying objects in images, the method comprising:

re-training one or more classification layers of one or more previously trained machine learning models;
extracting, from a received image, one or more images depicting regions of interest in the received image;
and
determining objects that appear in the one or more extracted images using, at least in part, the one or more previously trained machine learning models with the one or more re-trained classification layers.

1 more element

Dependencies are inferred from the claim text.

Method and system for determining objects depicted in images

Life of this patent

Method and system for determining objects depicted in images

Life of this patent

Abstract

Claims20