Supplymentary Materials for “FontRNN: Generating Large-scale Chinese Fonts via Recurrent Neural Network” reference

The main characteristics of soil deformation are a lowering in soil surface according to the shape of the object, the pres- ence of material below the object that will mark the

Our methodology allows generating large-scale fragment test data sets from existing CH object models, complementing manual benchmark generation based on scanning of fragmented

“FontRNN: Generating Large-scale Chinese Fonts via Recurrent Neural Network”. More character images generated by our method comparing with target images are

First, a novel motion descriptor that disentangles the standard pose representation by removing subject-specific features; second, a neural-network-based recurrent regressor

Keywords: radar, detection, constant false alarm rate (CFAR), clutter, Swerling targets, neural network.. A typical technique employed for this purpose is the constant false alarm

Using training data with labeled SPW-R events in real-world datasets from different sources we trained RippleNet instances to predict a continuous signal representing the time

Using training data with labeled SPW-R events in real-world datasets from different sources we trained RippleNet to predict a continuous signal representing the time varying

The framework is based on a recurrent neural network (RNNs) with the considered information plugged as input (information on the weather, and the context), and the historical