Abstract: The present invention discloses an image enlarging method having super resolution enlarging mechanism that includes the steps outlined below. An enlarging module of a neural network system receives an input image to generate an enlarged image. A front end convolutional path included in a neural network module of the neural network system receives the input image to perform convolution to generate a front end operation output result. Branching convolutional paths included in the neural network module respectively receive the front end operation output result to perform convolution to generate groups of output image residues. A mixing module of the neural network system weights the output image residues according to weighing settings related to image regions of the input image and mixes the weighted output image residues to generate a group of final output image residue such that an enhancement module enhances the enlarged image to generate an output enlarged image.

Abstract: The present invention discloses an image enlarging method having super resolution enlarging mechanism that includes the steps outlined below. An enlarging module of a neural network system receives an input image to generate an enlarged image. A front end convolutional path included in a neural network module of the neural network system receives the input image to perform convolution to generate a front end operation output result. Branching convolutional paths included in the neural network module respectively receive the front end operation output result to perform convolution to generate groups of output image residues. A mixing module of the neural network system weights the output image residues according to weighing settings related to image regions of the input image and mixes the weighted output image residues to generate a group of final output image residue such that an enhancement module enhances the enlarged image to generate an output enlarged image.

Abstract: A feeding analysis system of milk-production livestock includes a plurality of image analysis devices and a central server signally connected to each image analysis device. Each image analysis device is configured to capture a plurality of images of a feeding field, perform a clear processing on the images, identify a plurality of facial images of the plurality of milk-production livestock for feeding action from the cleared images and generate a plurality of capturing signals by capturing the plurality of facial images and a feeding duration corresponding to the facial images, and transmit the capturing signals to the central server. The central server is configured to receive the capturing signals, identify the milk-production livestock identities of the facial images of the corresponding capturing signal and generate a feeding record by integrating the identified milk-production livestock identity and the feeding duration of the capturing signal.