Handwriting Prediction Considering Inter-Class Bifurcation Structures

09/27/2020
by   Masaki Yamagata, et al.
0

Temporal prediction is a still difficult task due to the chaotic behavior, non-Markovian characteristics, and non-stationary noise of temporal signals. Handwriting prediction is also challenging because of uncertainty arising from inter-class bifurcation structures, in addition to the above problems. For example, the classes '0' and '6' are very similar in terms of their beginning parts; therefore it is nearly impossible to predict their subsequent parts from the beginning part. In other words, '0' and '6' have a bifurcation structure due to ambiguity between classes, and we cannot make a long-term prediction in this context. In this paper, we propose a temporal prediction model that can deal with this bifurcation structure. Specifically, the proposed model learns the bifurcation structure explicitly as a Gaussian mixture model (GMM) for each class as well as the posterior probability of the classes. The final result of prediction is represented as the weighted sum of GMMs using the class probabilities as weights. When multiple classes have large weights, the model can handle a bifurcation and thus avoid an inaccurate prediction. The proposed model is formulated as a neural network including long short-term memories and is thus trained in an end-to-end manner. The proposed model was evaluated on the UNIPEN online handwritten character dataset, and the results show that the model can catch and deal with the bifurcation structures.

READ FULL TEXT
research
06/24/2019

Sequential Neural Processes

Neural processes combine the strengths of neural networks and Gaussian p...
research
05/10/2022

A spatial-temporal short-term traffic flow prediction model based on dynamical-learning graph convolution mechanism

Short-term traffic flow prediction is a vital branch of the Intelligent ...
research
08/25/2022

Spatio-Temporal Representation Learning Enhanced Source Cell-phone Recognition from Speech Recordings

The existing source cell-phone recognition method lacks the long-term fe...
research
05/03/2022

Predicting vacant parking space availability zone-wisely: a graph based spatio-temporal prediction approach

Vacant parking space (VPS) prediction is one of the key issues of intell...
research
01/26/2019

GCN-GAN: A Non-linear Temporal Link Prediction Model for Weighted Dynamic Networks

In this paper, we generally formulate the dynamics prediction problem of...
research
02/22/2019

Towards Neural Mixture Recommender for Long Range Dependent User Sequences

Understanding temporal dynamics has proved to be highly valuable for acc...

Please sign up or login with your details

Forgot password? Click here to reset