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Found 3 papers, 1 papers with code
`BonTen' -- Corpus Concordance System for `NINJAL Web Japanese Corpus'
The National Institute for Japanese Language and Linguistics, Japan (NINJAL) has undertaken a corpus compilation project to construct a web corpus for linguistic research comprising ten billion words.
Non-iterative optimization of pseudo-labeling thresholds for training object detection models from multiple datasets
A popular approach to this problem is first to train teacher models and then to use their confident predictions as pseudo ground-truth labels when training a student model.
Evaluating generation of chaotic time series by convolutional generative adversarial networks
To understand the ability and limitations of convolutional neural networks to generate time series that mimic complex temporal signals, we trained a generative adversarial network consisting of deep convolutional networks to generate chaotic time series and used nonlinear time series analysis to evaluate the generated time series.
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