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Found 7 papers, 0 papers with code
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems
Deep learning (DL) defines a new data-driven programming paradigm that constructs the internal system logic of a crafted neuron network through a set of training data.
Model-based Deep Medical Imaging: the roadmap of generalizing iterative reconstruction model using deep learning
Usually, acquiring less data is a direct but important strategy to address these issues.
Quality Assessment of DIBR-synthesized views: An Overview
In this paper, we provide a comprehensive survey on various current approaches for DIBR-synthesized views.
Extensions of weak matroids over skew tracts and strong matroids over stringent skew hyperfields
We find a characterization of single-element extensions of strong matroids over stringent skew hyperfields.
Combinatorics Algebraic Geometry Rings and Algebras
Entity-Assisted Language Models for Identifying Check-worthy Sentences
Our results show that the neural language models significantly outperform traditional TF. IDF and LSTM methods.
Leveraging Users' Social Network Embeddings for Fake News Detection on Twitter
We conclude that the Twitter users' friendship and followers network information can significantly outperform language-based approaches, as well as the existing state-of-the-art fake news detection models that use a more sophisticated network structure, in classifying fake news on Twitter.
Model-driven CT reconstruction algorithm for nano-resolution X-ray phase contrast imaging
In conclusion, a novel model-driven nPCT image reconstruction algorithm with high accuracy and robustness is verified for the Lau interferometer based hard X-ray nano-resolution phase contrast imaging.
