Applied Recognition Corp.

Lg Electronics Inc.

University of Toronto

Konstantinos Plataniotis

Donald Craig Waugh

Yong Man Ro

Chris Studholme

Ray Ganong

Hyunwoo Kim

Sangmin Lee

Savvas Damaskinos

Jasper Hayes

Lyndon Chan

Mahdi S Hosseini

Shervin Mehryar

Mahesh Sudhakar

Sam Sattarzadeh

YeonJeong Jeong

Jongseong Jang

Anthony Lem

Embodiments of the present disclosure relate to generating explanation maps for explaining convolutional neural networks through attribution-based input sampling and block-wise feature aggregation. An example of a disclosed method for generating an explanation map for a convolutional neural network (CNN) includes obtaining an input image resulting in an output determination of the CNN, selecting a plurality of feature maps extracted from a plurality of pooling layers of the CNN, generating a plurality of attribution masks based on the plurality of feature maps, applying the generated attribution masks to the input image to obtain a plurality of visualization maps, and generating an explanation map of the output determination of the CNN based on the plurality of visualization maps.

Semantic input sampling for explanation (SISE) of convolutional neural networks

The present invention provides, in at least one aspect, methods and systems that detect at least one face in at least one digital image, determine and store area co-ordinates of a location of the at least one detected face in the at least one digital image, apply at least one transformation to the at least one detected face to create at least one portrait of the at least one detected face, rotate the at least one portrait at least until the at least one portrait is shown in a vertical orientation and a pair of eyes of the at least one face shown in the at least one portrait are positioned on a horizontal plane; and store the rotated at least one portrait.

Face detection and recognition

The present invention solves the problem of automatically recognizing multiple known faces in photos or videos on a local computer storage device (on a home computer). It further allows for sophisticated organization and presentation of the photos or videos based on the graphical selection of known faces (by selecting thumbnail images of people). It also solves the problem of sharing or distributing photos or videos in an automated fashion between 'friends' who are also using the same software that enables the invention. It further solves the problem of allowing a user of the invention to review the results of the automatic face detection, eye detection, and face recognition methods and to correct any errors resulting from the automated process.

Method, system, and computer program for identification and sharing of digital images with face signatures

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Toronto, Canada

Konstantinos Plataniotis