公开(公告)号：US20240394840A1

公开(公告)日：2024-11-28

申请号：US18669939

申请日：2024-05-21

Applicant: Google LLC

Inventor： Elchonon Zeav Lapin ,  Xibing Yang ,  Amit Handa ,  Apurv Suman ,  Siddhant Mittal ,  Ashish Dilipchand Bora ,  Thorne Wolfenbarger ,  Naga Sreenivas Meruva ,  Yudong Sun ,  Rahul Guin ,  Arie Sharon ,  Beatriz Alessio Robles Orozco ,  Yuanzhen Li ,  Zhongyue Zheng ,  Mohammad Izadi

IPC: G06T5/50 ,  G06T3/40 ,  G06T5/70 ,  G06T7/13 ,  G06T7/194 ,  G06T7/50 ,  H04N5/272

Abstract: Using artificial intelligence (AI), imagery may be created for content in response to verbal or textual input. The imagery includes an object, such as a product, and a quality of the image is improved using pre-processing techniques before the image is generated and post-processing techniques after the image is generated. The pre-processing may include upscaling the object in the original image, segmenting the object from its background in the captured image, adding an outline or border stroke to the object. The post-processing techniques may include removing the object from the AI-generated background while keeping shadows and other effects in place, blurring portions of the AI-generated background where the object will be positioned, removing the outline from the object, and re-positioning the object in the AI-generated background with the outline removed.

公开(公告)号：US20230230232A1

公开(公告)日：2023-07-20

申请号：US18011597

申请日：2021-11-02

Applicant: Google LLC

Inventor： Yun Liu ,  Naama Hammel ,  Akinori Mitani ,  Derek Janme Wu ,  Ashish Dilipchand Bora ,  Avinash Vaidyanathan Varadarajan ,  Boris Alekandrovich Babenko

IPC: G06T7/00 ,  G16H50/50 ,  G16H30/40 ,  A61B3/12

CPC classification number: G06T7/0012 ,  G16H50/50 ,  G16H30/40 ,  A61B3/1241 ,  G06T2207/30041 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: The present disclosure is directed to systems and methods that leverage machine learning for detection of eye or non-eye (e.g., systemic) diseases from external anterior eye images. In particular, a computing system can include and use one or more machine-learned disease detection models to provide disease predictions for a patient based on external anterior eye images of the patient. Specifically, in some example implementations, a computing system can obtain one or more external images that depict an anterior portion of an eye of a patient. The computing system can process the one or more external images with the one or more machine-learned disease detection models to generate a disease prediction for the patient relative to one or more diseases, including, as examples, diseases which present manifestations in a posterior of the eye (e.g., diabetic retinopathy) or systemic diseases (e.g., poorly controlled diabetes).