Abstract: A light-emitting device, including a first type semiconductor layer, a patterned insulating layer, a light-emitting layer, and a second type semiconductor layer, is provided. The patterned insulating layer covers the first type semiconductor layer and has a plurality of insulating openings. The insulating openings are separated from each other. The light-emitting layer is located in the plurality of insulating openings and covers a portion of the first type semiconductor layer. The second type semiconductor layer is located on the light-emitting layer.

Abstract: A computing device for handling anomaly detection, comprises an encoder, for receiving an input image, to generate a first latent vector comprising a semantic latent vector and a visual appearance latent vector according to the input image and at least one first parameter of the encoder; and a training module, coupled to the encoder, for receiving the input image and the first latent vector, to update the at least one first parameter according to the input image and the first latent vector and a loss function.

Abstract: A learning module for handling classification tasks, configured to perform the following instructions: receiving a first plurality of parameters from a training module; and generating a first loss of a first task in a first domain and a second loss of a second task in a second domain according to the first plurality of parameters.

Abstract: A computing device for handling anomaly detection, comprises an encoder, for receiving an input image, to generate a first latent vector comprising a semantic latent vector and a visual appearance latent vector according to the input image and at least one first parameter of the encoder; and a training module, coupled to the encoder, for receiving the input image and the first latent vector, to update the at least one first parameter according to the input image and the first latent vector and a loss function.

Abstract: A computing device for handling image super-resolution (ISR), comprises a generator module, for receiving at least one input image, to generate an output image according to at least one first parameter and a first plurality of feature maps generated by at least one first channel attention (CA); a discriminator module, for receiving the output image and a high resolution (HR) image, to generate a second plurality of feature maps and a third plurality of feature maps by at least one second CA, and to generate at least one score according to the second plurality of feature maps, the third plurality of feature maps and at least one second parameter; and a feedback module, for receiving the at least one score, to update the at least one first parameter and the at least one second parameter according to the at least one score and an objective function.

Abstract: A computing device for handling image super-resolution (ISR), comprises a generator module, for receiving at least one input image, to generate an output image according to at least one first parameter and a first plurality of feature maps generated by at least one first channel attention (CA); a discriminator module, for receiving the output image and a high resolution (HR) image, to generate a second plurality of feature maps and a third plurality of feature maps by at least one second CA, and to generate at least one score according to the second plurality of feature maps, the third plurality of feature maps and at least one second parameter; and a feedback module, for receiving the at least one score, to update the at least one first parameter and the at least one second parameter according to the at least one score and an objective function.

Abstract: A method for identifying vehicle license plate, comprising: mounting a server apparatus, and establishing a vehicle database and a vehicle license plate identification library in the server apparatus so as to generate a vehicle data and a vehicle license plate identification program; establishing a communication link, and receiving the vehicle data and the vehicle license plate identification program by the mobile device, and installing the vehicle license plate identification program and storing the vehicle data; capturing plate number of a vehicle by a camera module mounted in the mobile device for generating an image and then analyzing the plate number in the image by an analyzing program to generate an analysis result; comparing the analysis result with the vehicle data by a comparison module of the mobile device for generating a comparison result; and displaying the comparison result.