公开(公告)号：US20160171285A1

公开(公告)日：2016-06-16

申请号：US14965027

申请日：2015-12-10

Applicant: Samsung Electronics Co., Ltd.

Inventor： Irina KIM ,  Woong-hee LEE ,  Byeoung-su KIM

IPC: G06K9/00 ,  G06T7/40 ,  G06T5/40 ,  G06K9/46 ,  G06T3/40

CPC classification number: G06K9/00228 ,  G06K9/6203 ,  G06K9/6257 ,  G06K9/6292

Abstract: At least one example embodiment discloses a method of detecting an object in an image. The method includes receiving an image, generating first images for performing a first classification operation based on the received image, reviewing first-image features of the first images using a first feature extraction method with first-type features, first classifying at least some of the first images as second images, the classified first images having first-image features matching the first-type features, reviewing second-image features of the second images using a second feature extraction method with second-type features, second classifying at least some of the second images as third images, the classified second images having second-image features matching the second-type features and detecting an object in the received image based on results of the first and second classifying,

Abstract translation: 至少一个示例性实施例公开了一种检测图像中的对象的方法。 该方法包括接收图像，产生基于接收到的图像执行第一分类操作的第一图像，使用具有第一类型特征的第一特征提取方法来检查第一图像的第一图像特征，首先对 第一图像作为第二图像，分类的第一图像具有与第一类型特征匹配的第一图像特征，使用具有第二类型特征的第二特征提取方法来检查第二图像的第二图像特征，第二图像分类中的至少一些 第二图像作为第三图像，分类的第二图像具有与第二类型特征匹配的第二图像特征，并且基于第一和第二分类的结果来检测接收到的图像中的对象，

公开(公告)号：US20190147322A1

公开(公告)日：2019-05-16

申请号：US16044163

申请日：2018-07-24

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Do-yun KIM ,  Han-young YIM ,  Byeoung-su KIM ,  Nak-woo SUNG ,  Jong-han LIM ,  Sang-hyuck HA

IPC: G06N3/04 ,  G06N3/08 ,  G06F17/18

Abstract: An artificial neural network (ANN) quantization method for generating an output ANN by quantizing an input ANN includes: obtaining second parameters by quantizing first parameters of the input ANN; obtaining a sample distribution from an intermediate ANN in which the obtained second parameters have been applied to the input ANN; and obtaining a fractional length for the sample distribution by quantizing the obtained sample distribution.

公开(公告)号：US20190095777A1

公开(公告)日：2019-03-28

申请号：US16008275

申请日：2018-06-14

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Do-yun KIM ,  Han-young YIM ,  In-yup KANG ,  Byeoung-su KIM ,  Nak-woo SUNG ,  Jong-Han LIM ,  Sang-hyuck HA

IPC: G06N3/04 ,  G06N3/08

Abstract: A method of quantizing an artificial neural network includes dividing an input distribution of the artificial neural network into a plurality of segments, generating an approximated density function by approximating each of the plurality of segments, calculating at least one quantization error corresponding to at least one step size for quantizing the artificial neural network, based on the approximated density function, and determining a final step size for quantizing the artificial neural network based on the at least one quantization error.