We present an incremental syntactic representation that consists of assigning a single discrete label to each word in a sentence, where the label is predicted using strictly incremental processing of a prefix of the sentence, and the sequence of labels for a sentence fully determines a parse tree.
This paper introduces CiwaGAN, a model of human spoken language acquisition that combines unsupervised articulatory modeling with an unsupervised model of information exchange through the auditory modality.
Since manifold learning is used, the machine is shown to be robust against noise in the inputs (i. e. using hand-drawn images and noisy IDVG curves) and not confused by weak and irrelevant independent variables.
We also achieved significant accuracy with 1/4 sparse sampling to reduce any spatial correlations among data, suggesting that the model has the potential to be generalized to other regions for indirect estimation of geologic composition.
Successful material selection is critical in designing and manufacturing products for design automation.
(2) A mediated hybrid recognition system in which a system is created by combining independent modules that detect each semantic feature.
It provides a set of explainability tools (ET) that opens the black box of a DNN so that the individual contribution of neurons to category classification can be ranked and visualized.
We compared the performance between the auto-detection system and the human eye.
In summary, CycleGAN is used with synthetic data to improve the IR image conversion performance of visible images.
In the field of pattern recognition research, the method of using deep neural networks based on improved computing hardware recently attracted attention because of their superior accuracy compared to conventional methods.
Transcribing voice communications in NASA's launch control center is important for information utilization.
We used a deep learning based on conditional generative adversarial networks to train associations between the various images of flammable and hazardous objects and their partially occluded counterparts.