1. A learning method for improving image segmentation by using a learning device, wherein the learning device includes (i) an encoding layer having each of a (1-1)-th to a (1-K)-th filters respectively generating a (1-1)-th to a (1-K)-th feature maps by applying one or more convolution operations to a training image as an input image; (ii) a decoding layer having each of a (2-K)-th to a (2-1)-th filters respectively generating a (2-K)-th to a (2-1)-th feature maps by applying one or more deconvolution operations to the 1-K feature map; and (iii) a 1-st to an H-th loss layers respectively interacting with H filters among the K filters included in the decoding layer, comprising steps of: (a) the learning device, if the input image is obtained, acquiring or supporting another device to acquire the (2-K)-th to the (2-1)-th feature maps through the encoding layer and the decoding layer, and acquiring or supporting another device to acquire a 1-st to an H-th losses from the 1-st to the H-th loss layers respectively corresponding to each of H feature maps, obtained from the H selected filters, among the (2-K)-th to the (2-1)-th feature maps; and (b) the learning device, upon performing a backpropagation process, performing processes of (1) allowing the (2-M)-th filter to apply a convolution operation to an (M−1) 2 -th adjusted feature map relayed from the (2-(M−1))-th filter to thereby obtain an M 1 -th temporary feature map; and (2) relaying, to the (2-(M+1))-th filter, M 2 -th adjusted feature map obtained by computing the M-th loss with the M 1 -th temporary feature map and (3) adjusting at least part of parameters of the (1-1)-th to the (1-K)-th filters and the (2-K)-th to the (2-1)-th filters, where M is an integer greater than or equal to 2 and less than or equal to K−1, wherein, as an initial state of the step (b), the 1-st loss layer computes the 1-st loss corresponding to the (2-1)-th feature map, and the (2-1)-th filter applies a convolution operation to the 1-st loss to thereby acquire an l 2 -th adjusted feature map, and the (2-1)-th filter relays the l 2 -th adjusted feature map to the (2-2)-th filter.