Samsung Sds Co., Ltd.

Sun Ah Kang

Sang Hak Lee

Bo Youn Kim

Seong Jong Ha

Young Min Shin

Jong Hang Kim

Yeon Hee Kwon

Yu Ri Ahn

Provided is a machine learning-based object detection method performed by an object detection apparatus. the method comprises constructing an object detection model by performing machine learning on a training image set, wherein the object detection model is a model for detecting a target object in an input image based on the result of comparing a confidence score for the target object with a threshold value, obtaining an input image given a detection result for the target object, wherein the obtained input image is an image not included in the training image set, predicting one or more object regions, in which the target object exists, in the obtained input image by using the object detection model, classifying a region not matching the detection result among the predicted object regions as a false detection region; and adjusting the threshold value of the object detection model based on a confidence score of the false detection region.

Machine learning-based object detection method and apparatus

According to a first aspect of the present invention, a method for setting a region of interest may include: detecting a mark in an image frame photographed by a camera; and setting a region of interest using the detected mark.

Method and apparatus for setting region of interest

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Seoul, South Korea

Sun Ah Kang