AIMC Topic: Neural Networks, Computer

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Deep-learning-based 3D object salient detection via light-field integral imaging.

Optics letters
This Letter proposes an effective light-field 3D saliency object detection (SOD) method, which is inspired by the idea that the spatial and angular information inherent in a light-field implicitly contains the geometry and reflection characteristics ...

Optical random micro-phase-shift DropConnect in a diffractive deep neural network.

Optics letters
The formulation and training of unitary neural networks is the basis of an active modulation diffractive deep neural network. In this Letter, an optical random phase DropConnect is implemented on an optical weight to manipulate a jillion of optical c...

Feed-forward neural network as nonlinear dynamics integrator for supercontinuum generation: erratum.

Optics letters
We present an erratum to our Letter [Opt. Lett.47, 802 (2022)10.1364/OL.448571]. This erratum corrects an error in the sign of one of the higher-order dispersion coefficient used in the simulations of Figs. 2 and 4, as well as in Figs. S1 and S3. The...

Mass Deployment of Deep Neural Network: Real-Time Proof of Concept With Screening of Intracranial Hemorrhage Using an Open Data Set.

Neurosurgery
BACKGROUND: Intracranial hemorrhage (ICH) is considered an emergency that requires rapid medical or surgical management. Previous studies have used artificial intelligence to attempt to expedite the diagnosis of this pathology on neuroimaging. Howeve...

Deep Convolutional Neural Networks Implementation for the Analysis of Urine Culture.

Clinical chemistry
BACKGROUND: Urine culture images collected using bacteriology automation are currently interpreted by technologists during routine standard-of-care workflows. Machine learning may be able to improve the harmonization of and assist with these interpre...

Channel response-aware photonic neural network accelerators for high-speed inference through bandwidth-limited optics.

Optics express
Photonic neural network accelerators (PNNAs) have been lately brought into the spotlight as a new class of custom hardware that can leverage the maturity of photonic integration towards addressing the low-energy and computational power requirements o...

Noise-Transfer2Clean: denoising cryo-EM images based on noise modeling and transfer.

Bioinformatics (Oxford, England)
MOTIVATION: Cryo-electron microscopy (cryo-EM) is a widely used technology for ultrastructure determination, which constructs the 3D structures of protein and macromolecular complex from a set of 2D micrographs. However, limited by the electron beam ...

A deep dilated convolutional residual network for predicting interchain contacts of protein homodimers.

Bioinformatics (Oxford, England)
MOTIVATION: Deep learning has revolutionized protein tertiary structure prediction recently. The cutting-edge deep learning methods such as AlphaFold can predict high-accuracy tertiary structures for most individual protein chains. However, the accur...

DeepUMQA: ultrafast shape recognition-based protein model quality assessment using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Protein model quality assessment is a key component of protein structure prediction. In recent research, the voxelization feature was used to characterize the local structural information of residues, but it may be insufficient for descri...

Cross-dependent graph neural networks for molecular property prediction.

Bioinformatics (Oxford, England)
MOTIVATION: The crux of molecular property prediction is to generate meaningful representations of the molecules. One promising route is to exploit the molecular graph structure through graph neural networks (GNNs). Both atoms and bonds significantly...