AIMC Topic: Neural Networks, Computer

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Encoding of speech in convolutional layers and the brain stem based on language experience.

Scientific reports
Comparing artificial neural networks with outputs of neuroimaging techniques has recently seen substantial advances in (computer) vision and text-based language models. Here, we propose a framework to compare biological and artificial neural computat...

Accelerated submillimeter wave-encoded magnetic resonance imaging via deep untrained neural network.

Medical physics
BACKGROUND: Wave gradient encoding can adequately utilize coil sensitivity profiles to facilitate higher accelerations in parallel magnetic resonance imaging (pMRI). However, there are limitations in mainstream pMRI and a few deep learning (DL) metho...

Dynamic event-triggered controller design for nonlinear systems: Reinforcement learning strategy.

Neural networks : the official journal of the International Neural Network Society
The current investigation aims at the optimal control problem for discrete-time nonstrict-feedback nonlinear systems by invoking the reinforcement learning-based backstepping technique and neural networks. The dynamic-event-triggered control strategy...

Novel Molecular Representations Using Neumann-Cayley Orthogonal Gated Recurrent Unit.

Journal of chemical information and modeling
Advances in deep neural networks (DNNs) have made a very powerful machine learning method available to researchers across many fields of study, including the biomedical and cheminformatics communities, where DNNs help to improve tasks such as protein...

Complex computation from developmental priors.

Nature communications
Machine learning (ML) models have long overlooked innateness: how strong pressures for survival lead to the encoding of complex behaviors in the nascent wiring of a brain. Here, we derive a neurodevelopmental encoding of artificial neural networks th...

Dual-Encoder VAE-GAN With Spatiotemporal Features for Emotional EEG Data Augmentation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The current data scarcity problem in EEG-based emotion recognition tasks leads to difficulty in building high-precision models using existing deep learning methods. To tackle this problem, a dual encoder variational autoencoder-generative adversarial...

Use of a deep learning algorithm for non-mass enhancement on breast MRI: comparison with radiologists' interpretations at various levels.

Japanese journal of radiology
PURPOSE: To evaluate the diagnostic performance of deep learning using the Residual Networks 50 (ResNet50) neural network constructed from different segmentations for distinguishing malignant and benign non-mass enhancement (NME) on breast magnetic r...

Deformable registration of lung 3DCT images using an unsupervised heterogeneous multi-resolution neural network.

Medical & biological engineering & computing
Lung image registration is more challenging than other organs. This is because the breath of the human body causes large deformations in the lung parenchyma and small deformations in tissues such as the pulmonary vascular. Many studies have recently ...

Remix: Towards the transferability of adversarial examples.

Neural networks : the official journal of the International Neural Network Society
Deep neural networks (DNNs) are susceptible to adversarial examples, which are crafted by deliberately adding some human-imperceptible perturbations on original images. To explore the vulnerability of models of DNNs, transfer-based black-box attacks ...

Lightweight multi-scale classification of chest radiographs via size-specific batch normalization.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Convolutional neural networks are widely used to detect radiological findings in chest radiographs. Standard architectures are optimized for images of relatively small size (for example, 224 × 224 pixels), which suffices for...