In computer vision, two broad approaches to image in- painting exist: patch matching using low-level image fea- tures and feed-forward generative models with deep convo- lutional networks. The former approach [3, 8, 9] can syn- thesize plausible stationary textures, but usually makes c...
positional encodings have on encoding non-local context. Typically, if a relative positional encoding is learned accurately, the gating mechanism will assign it high weight compared to the ones which are not learned accurately. Fig2(c) illustrates the feed-forward in a typical gated axial ...
they lack the ability to model long-range dependencies present in an image. More precisely, in ConvNets each convolutional kernel attends to only a local-subset of pixels in the whole image and forces the network to focus on local patterns rather than the global context. There...
Inspired by ResNet, residual convolution module (RCM) is introduced as the basic processing unit to ease the training of the network. As shown in the bottom-left corner of Figure 2, there is an identity mapping between the input and output of the module. In the forward propagation, input ...
It is a feed-forward neural network widely used in image recognition and computer vision tasks. CNN was initially found to be very effective in processing pixel data and has translation invariance. CNN consists of multiple convolutional layers and pooling layers, each performing specific operations. ...
It is a feed-forward neural network widely used in image recognition and computer vision tasks. CNN was initially found to be very effective in processing pixel data and has translation invariance. CNN consists of multiple convolutional layers and pooling layers, each performing specific operations. ...
A feedforward neural network was used to forecast the voltage and the outlet temperature, and the prediction errors are around 9.4% and 5.6% [16,17]. Moreover, methods such as least-squares SVM (LSSVM) [18], relevance vector machine (RVM) [19], the grey model [20], the summation ...