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Found 7 papers, 3 papers with code
Training-free image style alignment for self-adapting domain shift on handheld ultrasound devices
Moreover, the models trained on standard ultrasound device data are constrained by training data distribution and perform poorly when directly applied to handheld device data.
An Association Test Based on Kernel-Based Neural Networks for Complex Genetic Association Analysis
The advent of artificial intelligence, especially the progress of deep neural networks, is expected to revolutionize genetic research and offer unprecedented potential to decode the complex relationships between genetic variants and disease phenotypes, which could mark a significant step toward improving our understanding of the disease etiology.
A Kernel-Based Neural Network Test for High-dimensional Sequencing Data Analysis
While DNN plays a central role in modern AI technology, it has been rarely used in sequencing data analysis due to challenges brought by high-dimensional sequencing data (e. g., overfitting).
Human-Inspired Facial Sketch Synthesis with Dynamic Adaptation
Besides, different artists may use diverse drawing techniques and create multiple styles of sketches; but the style is globally consistent in a sketch.
Semantic-aware Generation of Multi-view Portrait Drawings
Our motivation is that facial semantic labels are view-consistent and correlate with drawing techniques.
Masked and Adaptive Transformer for Exemplar Based Image Translation
To overcome this challenge, we improve the accuracy of matching on the one hand, and diminish the role of matching in image generation on the other hand.
A Sieve Quasi-likelihood Ratio Test for Neural Networks with Applications to Genetic Association Studies
Neural networks (NN) play a central role in modern Artificial intelligence (AI) technology and has been successfully used in areas such as natural language processing and image recognition.
