AIMC Topic: Neural Networks, Computer

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A multi-scale convolutional neural network for phenotyping high-content cellular images.

Bioinformatics (Oxford, England)
MOTIVATION: Identifying phenotypes based on high-content cellular images is challenging. Conventional image analysis pipelines for phenotype identification comprise multiple independent steps, with each step requiring method customization and adjustm...

Image-based surrogate biomarkers for molecular subtypes of colorectal cancer.

Bioinformatics (Oxford, England)
MOTIVATION: Whole genome expression profiling of large cohorts of different types of cancer led to the identification of distinct molecular subcategories (subtypes) that may partially explain the observed inter-tumoral heterogeneity. This is also the...

Biological modelling of a computational spiking neural network with neuronal avalanches.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
In recent years, an increasing number of studies have demonstrated that networks in the brain can self-organize into a critical state where dynamics exhibit a mixture of ordered and disordered patterns. This critical branching phenomenon is termed ne...

Predicting protein-protein interactions from protein sequences by a stacked sparse autoencoder deep neural network.

Molecular bioSystems
Protein-protein interactions (PPIs) play an important role in most of the biological processes. How to correctly and efficiently detect protein interaction is a problem that is worth studying. Although high-throughput technologies provide the possibi...

Automatic phase aberration compensation for digital holographic microscopy based on deep learning background detection.

Optics express
We propose a fully automatic technique to obtain aberration free quantitative phase imaging in digital holographic microscopy (DHM) based on deep learning. The traditional DHM solves the phase aberration compensation problem by manually detecting the...

Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging.

Journal of biomedical optics
Surgical cancer resection requires an accurate and timely diagnosis of the cancer margins in order to achieve successful patient remission. Hyperspectral imaging (HSI) has emerged as a useful, noncontact technique for acquiring spectral and optical p...

Pavement type and wear condition classification from tire cavity acoustic measurements with artificial neural networks.

The Journal of the Acoustical Society of America
Tire road noise is the major contributor to traffic noise, which leads to general annoyance, speech interference, and sleep disturbances. Standardized methods to measure tire road noise are expensive, sophisticated to use, and they cannot be applied ...

Convolutional neural network-based automatic classification of midsagittal tongue gestural targets using B-mode ultrasound images.

The Journal of the Acoustical Society of America
Tongue gestural target classification is of great interest to researchers in the speech production field. Recently, deep convolutional neural networks (CNN) have shown superiority to standard feature extraction techniques in a variety of domains. In ...

Auditory feature representation using convolutional restricted Boltzmann machine and Teager energy operator for speech recognition.

The Journal of the Acoustical Society of America
In this letter, authors propose an auditory feature representation technique with the filterbank learned using an annealing dropout convolutional restricted Boltzmann machine (ConvRBM) and noise-robust energy estimation using the Teager energy operat...