公开(公告)号：US12300007B1

公开(公告)日：2025-05-13

申请号：US17957360

申请日：2022-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Ilya Levner ,  Aditya Ghuge ,  Tabrez Mohammed

IPC: G06V20/70 ,  G06V10/26 ,  G06V10/74 ,  G06V20/50

Abstract: Techniques are generally described for cropped image evaluation. In various examples, first image data representing a first image and second image data representing a cropped version of the first image may be received. An image captioning model may be used to generate first text data describing the first image data and second text data describing the second image data. A first encoder may be used to generate first data representing the first text data and second data representing the second text data. In various examples, a third data representing a degree of similarity between the first data and the second data may be generated. In some cases, first computer-executable instructions configured to cause the second image data to be displayed on a display may be generated based at least in part on the third data.

公开(公告)号：US11354936B1

公开(公告)日：2022-06-07

申请号：US16929387

申请日：2020-07-15

Applicant: Amazon Technologies, Inc.

Inventor： Dharmil Satishbhai Chandarana ,  Ilya Levner ,  Zhaoqing Ma ,  Prajwal Yadapadithaya ,  Riley James Williams ,  Canku Alp Calargun ,  Prama Anand

IPC: G06V40/00 ,  G06V40/16 ,  G06K9/62

Abstract: Techniques for improved image classification are provided. Face embeddings are generated for each face depicted in a collection of images, and the face embeddings are clustered based on the individual whose face is depicted. Based on these clusters, each embedding is assigned a label reflecting the cluster assignments. Some or all of the face embeddings are then used to train a classifier model to generate cluster labels for new input images. This classifier model can then be used to process new images in an efficient manner, and classify them into appropriate clusters.

公开(公告)号：US11003959B1

公开(公告)日：2021-05-11

申请号：US16440384

申请日：2019-06-13

Applicant: AMAZON TECHNOLOGIES, INC.

Inventor： Ilya Levner ,  Konstantinos Boulis ,  Gurbinder Gill ,  Canku Calargun ,  Prajwal Yadapadithaya ,  Venkata Krishnan Ramamoorthy ,  Zhaoqing Ma

IPC: G06K9/62 ,  G06N3/04 ,  G06N3/08 ,  G06K9/68

Abstract: Categorizing images may include training a first neural network to cluster a plurality of images to obtain a first image embedding space, wherein a vector representation is determined for each of the plurality of images based on the training, determining a vector norm value corresponding to each of the plurality of images based on the vector representation for each of the plurality of images, and identifying a first subset of the images for which a corresponding vector norm value satisfies a predetermined vector norm quality threshold. Then, a second neural network may be trained using the first subset of images to obtain a second image embedding space, and the second image embedding space may be used to categorize additional images.