AIMC Topic: Neural Networks, Computer

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Exponential synchronization of memristive neural networks with time-varying delays via quantized sliding-mode control.

Neural networks : the official journal of the International Neural Network Society
In the paper, exponential synchronization issue is considered for memristive neural networks (MNNs) with time-varying delays via quantized sliding-mode algorithm. Quantized Sliding-mode controller is introduced to ensure the slave system can be expon...

Three-Dimensional Convolutional Neural Network for Prostate MRI Segmentation and Comparison of Prostate Volume Measurements by Use of Artificial Neural Network and Ellipsoid Formula.

AJR. American journal of roentgenology
The purposes of this study were to assess the performance of a 3D convolutional neural network (CNN) for automatic segmentation of prostates on MR images and to compare the volume estimates from the 3D CNN with those of the ellipsoid formula. The s...

Deciphering anomalous heterogeneous intracellular transport with neural networks.

eLife
Intracellular transport is predominantly heterogeneous in both time and space, exhibiting varying non-Brownian behavior. Characterization of this movement through averaging methods over an ensemble of trajectories or over the course of a single traje...

Automated classification of three-dimensional reconstructions of coral reefs using convolutional neural networks.

PloS one
Coral reefs are biologically diverse and structurally complex ecosystems, which have been severally affected by human actions. Consequently, there is a need for rapid ecological assessment of coral reefs, but current approaches require time consuming...

Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities.

NMR in biomedicine
Quantitative susceptibility mapping (QSM) has gained broad interest in the field by extracting bulk tissue magnetic susceptibility, predominantly determined by myelin, iron and calcium from magnetic resonance imaging (MRI) phase measurements in vivo....

Searching for structure in collective systems.

Theory in biosciences = Theorie in den Biowissenschaften
From fish schools and bird flocks to biofilms and neural networks, collective systems in nature are made up of many mutually influencing individuals that interact locally to produce large-scale coordinated behavior. Although coordination is central t...

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI.

IEEE journal of biomedical and health informatics
Brain Metastases (BM) complicate 20-40% of cancer cases. BM lesions can present as punctate (1 mm) foci, requiring high-precision Magnetic Resonance Imaging (MRI) in order to prevent inadequate or delayed BM treatment. However, BM lesion detection re...

Deep Neural Oracles for Short-Window Optimized Compressed Sensing of Biosignals.

IEEE transactions on biomedical circuits and systems
The recovery of sparse signals given their linear mapping on lower-dimensional spaces can be partitioned into a support estimation phase and a coefficient estimation phase. We propose to estimate the support with an oracle based on a deep neural netw...

Semiconductor Quantum Dots for Memories and Neuromorphic Computing Systems.

Chemical reviews
The continued growth in the demand of data storage and processing has spurred the development of high-performance storage technologies and brain-inspired neuromorphic hardware. Semiconductor quantum dots (QDs) offer an appealing option for these appl...

Predicting Optimal Hypertension Treatment Pathways Using Recurrent Neural Networks.

International journal of medical informatics
BACKGROUND: In ambulatory care settings, physicians largely rely on clinical guidelines and guideline-based clinical decision support (CDS) systems to make decisions on hypertension treatment. However, current clinical evidence, which is the knowledg...