This study aims to restore grating lobe artifacts and improve the image resolution of sparse array ultrasonography via a deep learning predictive model. A deep learning assisted sparse array was developed using only 64 or 16 channels out of the 128 c...
DNA methylation is a crucial topic in bioinformatics research. Traditional wet experiments are usually time-consuming and expensive. In contrast, machine learning offers an efficient and novel approach. In this study, we propose DeepMethylation, a no...
Neural networks : the official journal of the International Neural Network Society
37167751
We prove new generalization bounds for stochastic gradient descent when training classifiers with invariances. Our analysis is based on the stability framework and covers both the convex case of linear classifiers and the non-convex case of homogeneo...
Neural networks : the official journal of the International Neural Network Society
37441909
Deep neural networks are sensitive to adversarial examples and would produce wrong results with high confidence. However, most existing attack methods exhibit weak transferability, especially for adversarially trained models and defense models. In th...
Neural networks : the official journal of the International Neural Network Society
37418860
Image registration is a fundamental problem in computer vision and robotics. Recently, learning-based image registration methods have made great progress. However, these methods are sensitive to abnormal transformation and have insufficient robustnes...
Neural networks : the official journal of the International Neural Network Society
37839332
Humans and other animals navigate different environments effortlessly, their brains rapidly and accurately generalizing across contexts. Despite recent progress in deep learning, this flexibility remains a challenge for many artificial systems. Here,...
What is the optimal penalty for errors in infant skill learning? Behavioral analyses indicate that errors are frequent but trivial as infants acquire foundational skills. In learning to walk, for example, falling is commonplace but appears to incur o...
Neural networks : the official journal of the International Neural Network Society
38039683
From the perspective of input features, information can be divided into independent information and correlation information. Current neural networks mainly concentrate on the capturing of correlation information through connection weight parameters s...
Proceedings of the National Academy of Sciences of the United States of America
37695904
Research in both ecology and AI strives for predictive understanding of complex systems, where nonlinearities arise from multidimensional interactions and feedbacks across multiple scales. After a century of independent, asynchronous advances in comp...
Neural networks : the official journal of the International Neural Network Society
38113718
The 6-Degree-of-Freedom (6-DoF) robotic grasping is a fundamental task in robot manipulation, aimed at detecting graspable points and corresponding parameters in a 3D space, i.e affordance learning, and then a robot executes grasp actions with the de...