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Element Ai Inc.

Pedro Henrique Oliveira Pinheiro

Issam Hadj Laradji

Negar Rostamzadeh

Mark William Schmidt

David Maria Vazquez Bermudez

Systems and methods for addressing the cross domain issue using a similarity based classifier convolutional neural network. An input image is passed through a convolutional neural network that extracts its features. These features are compared to features of multiple sets of prototype representations with each set of prototype representations being extracted from and representing a category of images. The similarity between the features of the input image and features of the various prototype representations is scored and the prototype representation whose features are most similar to the features of the input image will have its label applied to the input image. The classifier is trained using images from a source domain and the input images are from a target domain. The training for the classifier is such that the classifier will be unable to determine if a specific data point is from the source domain or from the target domain.

Unsupervised domain adaptation with similarity learning for images

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.

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Montreal, Canada

Pedro Henrique Oliveira Pinheiro