Landing Ai

Sanjeev Satheesh

Gopi Prashanth Gopal

Dongyan Wang

Yiwen Rong

Andrew Yan-Tak Ng

Yu Qing Zhou

Pingyang He

Karthikeyan Thiruppathisamy Nathillvar

Rustam Hashimov

Dillon Anthony Laird

Alejandro Betancourt

Mark William Sabini

Ankur Rawat

Wei Fu

Rahul Devraj Solanki

Yuanzhe Dong

Hao Sheng

A process and a system for creating a visual guide for developing training data for a classification of image, where the training data includes images tagged with labels for the classification of the images. A processor may prompt a user to define a framework for the classification. For an initial set of images within the training data, qualified human classifiers are prompted to locate the images within the framework and to tag the images with labels. The processor determines whether the tagged images have consistent labels, and, if so, the processor adds images to the training data. The processor may add the images by providing a visual guide, the visual guide including tagged images arranged according to their locations within the framework their labels, and prompting human classifiers to tag the additional images with labels for the classification, according to the visual guide.

User-generated visual guide for the classification of images

A processor receives an image of a syringe. After identifying a background and foreground of the image, where the foreground indicates pixels that may be associated with a defect, the processor subtracts the background to generate an updated image with an accentuated foreground. The processor applies a bounding box to a group of pixels in the foreground and inputs the bounding box into a classifier. The classifier outputs a label indicating whether the syringe is defective.

Automated visual inspection of syringes

Growing community of inventors

Mountain View, CA, United States of America

Sanjeev Satheesh