Abstract: A control method of a fastening tool for fastening a component part includes photographing a fastening portion of the component part through a camera portion mounted on the fastening tool. The control method includes pre-processing that rotates an input image, which has been photographed by the camera portion, to match with representative model image. The control method includes estimating the fastening portion through an inference process through a convolutional neural network (CNN) algorithm-based image classification work on a video input image of a same fastening portion finished with the pre-processing work. The control method also includes setting a torque value that is matched with a recognized fastening portion when a probability value of the fastening portion in the inference process exceeds a predetermined reference ratio.

Abstract: Provided is a device for upscaling resolution based on a slice image, in which a low-resolution image is divided into a plurality of slice images so that a high-resolution image is generated. The device includes a convolution operation unit configured to convert a low-resolution input slice image into a high-resolution output slice image using a convolutional neural network. The convolutional neural network includes a cascading block configured to perform a convolution operation using a convolution filter having a predetermined size and a residual operation on an input feature map generated from the low-resolution input slice image to generate an output feature map, and an upscaling block configured to upscale the output feature map to generate the high-resolution output slice image.

Abstract: A control method of a fastening tool for fastening a component part includes photographing a fastening portion of the component part through a camera portion mounted on the fastening tool. The control method includes pre-processing that rotates an input image, which has been photographed by the camera portion, to match with representative model image. The control method includes estimating the fastening portion through an inference process through a convolutional neural network (CNN) algorithm-based image classification work on a video input image of a same fastening portion finished with the pre-processing work. The control method also includes setting a torque value that is matched with a recognized fastening portion when a probability value of the fastening portion in the inference process exceeds a predetermined reference ratio.

Abstract: A fastening tool system for fastening a component part by using a supplied power includes: a camera portion mounted on a fastening tool to photograph a fastening portion of the component part; an image input portion for inputting an image photographed from the camera portion when a distance with the fastening portion measured through a distance measurement sensor is within a predetermined distance; a communication portion for transmitting data by wireless communication; and a fastening portion determining portion that recognizes the fastening portion through machine learning algorithm-based image classification work for an input image of the camera portion and sets a torque value matched with the recognized fastening portion.

Abstract: Provided is a device for upscaling resolution based on a slice image, in which a low-resolution image is divided into a plurality of slice images so that a high-resolution image is generated. The device includes a convolution operation unit configured to convert a low-resolution input slice image into a high-resolution output slice image using a convolutional neural network. The convolutional neural network includes a cascading block configured to perform a convolution operation using a convolution filter having a predetermined size and a residual operation on an input feature map generated from the low-resolution input slice image to generate an output feature map, and an upscaling block configured to upscale the output feature map to generate the high-resolution output slice image.

Abstract: A fastening tool system for fastening a component part by using a supplied power includes: a camera portion mounted on a fastening tool to photograph a fastening portion of the component part; an image input portion for inputting an image photographed from the camera portion when a distance with the fastening portion measured through a distance measurement sensor is within a predetermined distance; a communication portion for transmitting data by wireless communication; and a fastening portion determining portion that recognizes the fastening portion through machine learning algorithm-based image classification work for an input image of the camera portion and sets a torque value matched with the recognized fastening portion.

Abstract: An image processing apparatus for transforming a wide-angle image into a narrow-angle image includes a deblurrer performing deblurring on the wide-angle image to generate a deblurred image; a super-resolution (SR) unit performing SR processing on the deblurred image to generate an upscaled transformed image; and a view transformer performing view transformation to obtain the narrow-angle image based on the wide-angle image and the upscaled transformed image.

Abstract: An image processing apparatus for transforming a wide-angle image into a narrow-angle image includes a deblurrer performing deblurring on the wide-angle image to generate a deblurred image; a super-resolution (SR) unit performing SR processing on the deblurred image to generate an upscaled transformed image; and a view transformer performing view transformation to obtain the narrow-angle image based on the wide-angle image and the upscaled transformed image.