Patent ID: 11886480
Assignee: ADOBE INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 2:
3. The method of claim 1, wherein the gated convolutional encoder-decoder model is jointly trained using a weighted auto-encoder loss associated with a reconstruction engine and a weighted classification loss associated with the supervised classification engine, further comprising jointly training the gated convolutional encoder-decoder model by:
encoding, by the gated convolutional encoder, training data to generate an initial latent representation of the training data;
training, by the reconstruction engine, the gated convolutional encoder-decoder model to reduce the weighted auto-encoder loss associated with decoding the initial latent representation of the training data; and
training, by the supervised classification engine, the gated convolutional encoder-decoder model to reduce the weighted classification loss associated with predicting an affect classification of the training data, wherein jointly training the gated convolutional encoder-decoder model comprises balancing a first weight attributed to the weighted auto-encoder loss and a second weight attributed to the weighted classification loss.