Deep Learning Platforms for Automated Visual Inspection

    公开(公告)号:US20230196096A1

    公开(公告)日:2023-06-22

    申请号:US17923347

    申请日:2021-04-30

    Applicant: AMGEN INC.

    CPC classification number: G06N3/08 G06F9/5027

    Abstract: Techniques that facilitate the development and/or modification of an automated visual inspection (AVI) system that implements deep learning are described herein. Some aspects facilitate the generation of a large and diverse training image library, such as by digitally modifying images of real-world containers, and/or generating synthetic container images using a deep generative model. Other aspects decrease the use of processing resources for training, and/or making inferences with, neural networks in an AVI system, such as by automatically reducing the pixel sizes of training images (e.g., by down-sampling and/or selectively cropping container images). Still other aspects facilitate the testing or qualification of an AVI neural network by automatically analyzing a heatmap or bounding box generated by the neural network. Various other techniques are also described herein.

    Systems and Methods for Automated In-Line Plunger Depth Measurement

    公开(公告)号:US20220261977A1

    公开(公告)日:2022-08-18

    申请号:US17670745

    申请日:2022-02-14

    Applicant: AMGEN INC.

    Abstract: An automated inspection system includes a sensor system that includes a sensor and is configured to generate a plurality of syringe scans by scanning each of a plurality of syringes. Each of the plurality of syringe scans is indicative of distance relative to the sensor. The automated inspection system also includes one or more processors configured to, for each of the plurality of syringes, analyze the respective syringe scan to determine (i) a first distance to a first portion (e.g., flange) of the syringe and (ii) a second distance to a second portion (e.g., plunger) of the syringe, and calculate a distance between the first and second portions based on the first distance and the second distance.

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