Patent ID: 11908103
Assignee: TENCENT AMERICA LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 3:
4. The method according to claim 1,
wherein weight coefficients of at least one of the feature learning DNN and the upscaling DNN comprise a 5-dimensional (5D) tensor with a size of c1, k1, k2, k3, c2,
wherein an input of a layer of the at least one of the feature learning DNN and the upscaling DNN comprises a 4-dimensional (4D) tensor A with a size of h1, w1, d1, c1,
wherein an output of the layer is a 4D tensor B with a size of h2, w2, d2, c2, and
wherein each of c1, k1, k2, k3, c2, h1, w1, d1, c1, h2, w2, d2, and c2 are integer numbers greater than or equal to 1,
wherein h1, w1, d1 are a height, a weight, and a depth of the tensor A,
wherein h2, w2, d2 are a height, a weight, and a depth of the tensor B,
wherein c1 and c2 are numbers of input and output channels respectively, and
wherein k1, k2, k3 are sizes of a convolution kernel and correspond to height, weight, and depth axes respectively.