Moxa Inc.

Wei-Yu Lee

Yu-Chiang Wang

Po-Yu Chuang

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.

Device and method of handling anomaly detection

A computing device for handling video content analysis, comprises a preprocessing module, for receiving a first plurality of frames and for determining whether to delete at least one of the first plurality of frames according to an event detection, to generate a second plurality of frames according to the determination for the first plurality of frames; a first deep learning module, for receiving the second plurality of frames and for determining whether to delete at least one of the second plurality of frames according to a plurality of features of the second plurality of frames, to generate a third plurality of frames according to the determination for the second plurality of frames; and a second deep learning module, for receiving the third plurality of frames, to generate a plurality of prediction outputs of the third plurality of frames.

Device and method of handling video content analysis

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.

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Taipei, Taiwan

Wei-Yu Lee