Element Ai Inc.

Servicenow, Inc.

Issam Hadj Laradji

David Vazquez Bermudez

Negar Rostamzadeh

Pedro Henrique Oliveira Pinheiro

David Maria Vazquez Bermudez

Mark William Schmidt

Pau Rodriguez Lopez

Rafael Pardinas

A method for training a machine learning localization model to localize objects belonging to a given class within an image, the method comprising: receiving images each comprising objects of the given class; and for each image: receiving a heat map generated using the machine learning localization model; identifying proposals each corresponding to a potential object, each proposal having associated thereto an initial probability that the proposal corresponds to the potential object; for each proposal, correcting the initial probability using the heat map; selecting given ones of the proposals having a greatest corrected probability, thereby identifying object candidates; and calculating a loss for the machine learning localization model based on a location of the object candidates within the training image and the heat map; and providing the calculated loss to the machine learning localization model.

Method and system for localization with supervision

A method and a system for generating training images for training an instance segmentation machine learning algorithm (MLA). A set of image-level labelled images are received, where a given image is labelled with a label indicative of a presence of an object having an object class in the image. A classification MLA detects the object having the object class in each image. A class activation map (CAM) indicative of discriminative regions used by the classification MLA for detecting the object in each image is generated. A region proposal MLA is used to generate region proposals for each image. A pseudo mask of the respective object is generated based on the region proposals and the CAM, where a pseudo mask is indicative of pixels corresponding to the respective object class. The pseudo masks are used as a label with the image-level labelled images for training the instance segmentation MLA.

Method of and system for generating training images for instance segmentation machine learning algorithm

Systems and methods for counting objects in images based on each object's approximate location in the images. An image is passed to a segmentation module. The segmentation module segments the image into at least one object blob. Each object blob is an indication of a single object. The object blobs are counted by a counting module. In some embodiments, the segmentation module segments the image by classifying each image pixel and grouping nearby pixels of the same class together. In some embodiments, the segmentation module comprises a neural network that is trained to group pixels based on a set of training images. A plurality of the training images contain at least one point marker corresponding to a single training object. The segmentation module learns to group pixels into training object blobs that each contain a single point marker. Each training object blob is thus an indication of a single object.

Counting objects in images based on approximate locations

Growing community of inventors

Montreal, Canada

Issam Hadj Laradji