公开(公告)号：US20230282193A1

公开(公告)日：2023-09-07

申请号：US18177885

申请日：2023-03-03

Applicant: University of Manitoba

Inventor： YOUNG JIN CHA ,  SUKHPREET SINGH BENIPAL

IPC: G10K11/178

CPC classification number: G10K11/1781 ,  G10K11/1785

Abstract: A computer-implemented method for generating anti-noise using an anti-noise generator to suppress noise from a noise source in an environment comprises processing a sound signal, which is representative of ambient sound including noise, anti-noise and propagation noise from the environment, using a deep learning algorithm configured to generate an anti-noise signal to form anti-noise. The deep learning algorithm comprises a convolution layer; after the convolution layer, a series of atrous scaled convolution modules, wherein each of the atrous scaled convolution modules comprises an atrous convolution, a nonlinear activation function after the atrous convolution, and a pointwise convolution after the nonlinear activation function; after the series of atrous scaled convolution modules, a recurrent neural network; and after the recurrent neural network, a plurality of fully connected layers.

公开(公告)号：US20220366682A1

公开(公告)日：2022-11-17

申请号：US17735507

申请日：2022-05-03

Applicant: UNIVERSITY OF MANITOBA

Inventor： YOUNG JIN CHA ,  DONGHO KANG

IPC: G06V10/82 ,  G06V10/77 ,  G06V10/771 ,  G06V10/26 ,  G06V10/80 ,  G06T7/00

Abstract: A computer-implemented method for analyzing an image to detect an article of interest (AOI) comprises processing the image using a machine learning algorithm configured to detect the AOI and comprising a convolutional neural network (CNN); and displaying the image with location of the AOI being indicated if determined to be present. The CNN comprises an input module configured to receive the image and comprising at least one convolutional layer, batch normalization and a nonlinear activation function; an encoder thereafter and configured to extract features indicative of a present AOI to form a feature map; a decoder thereafter and configured to discard features from the feature map that are not associated with the present AOI and to revert the feature map to a size matching an initial image size; and a concatenation module configured to link outputs of the input module, the encoder and the decoder for subsequent segmentation.