AIMC Topic: Neural Networks, Computer

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Universal Nonlinear Spiking Neural P Systems with Delays and Weights on Synapses.

Computational intelligence and neuroscience
The nonlinear spiking neural P systems (NSNP systems) are new types of computation models, in which the state of neurons is represented by real numbers, and nonlinear spiking rules handle the neuron's firing. In this work, in order to improve computi...

DeepAtrophy: Teaching a neural network to detect progressive changes in longitudinal MRI of the hippocampal region in Alzheimer's disease.

NeuroImage
Measures of change in hippocampal volume derived from longitudinal MRI are a well-studied biomarker of disease progression in Alzheimer's disease (AD) and are used in clinical trials to track therapeutic efficacy of disease-modifying treatments. Howe...

Multi-model CNN fusion for sperm morphology analysis.

Computers in biology and medicine
Infertility is a common disorder affecting 20% of couples worldwide. Furthermore, 40% of all cases are related to male infertility. The first step in the determination of male infertility is semen analysis. The morphology, concentration, and motility...

EMONAS-Net: Efficient multiobjective neural architecture search using surrogate-assisted evolutionary algorithm for 3D medical image segmentation.

Artificial intelligence in medicine
Deep learning plays a critical role in medical image segmentation. Nevertheless, manually designing a neural network for a specific segmentation problem is a very difficult and time-consuming task due to the massive hyperparameter search space, long ...

Indoor Positioning Using Magnetic Fingerprint Map Captured by Magnetic Sensor Array.

Sensors (Basel, Switzerland)
By collecting the magnetic field information of each spatial point, we can build a magnetic field fingerprint map. When the user is positioning, the magnetic field measured by the sensor is matched with the magnetic field fingerprint map to identify ...

Improving Animal Monitoring Using Small Unmanned Aircraft Systems (sUAS) and Deep Learning Networks.

Sensors (Basel, Switzerland)
In recent years, small unmanned aircraft systems (sUAS) have been used widely to monitor animals because of their customizability, ease of operating, ability to access difficult to navigate places, and potential to minimize disturbance to animals. Au...

Wireless Signal Propagation Prediction Based on Computer Vision Sensing Technology for Forestry Security Monitoring.

Sensors (Basel, Switzerland)
In this paper, Computer Vision (CV) sensing technology based on Convolutional Neural Network (CNN) is introduced to process topographic maps for predicting wireless signal propagation models, which are applied in the field of forestry security monito...

PRPI-SC: an ensemble deep learning model for predicting plant lncRNA-protein interactions.

BMC bioinformatics
BACKGROUND: Plant long non-coding RNAs (lncRNAs) play vital roles in many biological processes mainly through interactions with RNA-binding protein (RBP). To understand the function of lncRNAs, a fundamental method is to identify which types of prote...

Modeling learner-controlled mental model learning processes by a second-order adaptive network model.

PloS one
Learning knowledge or skills usually is considered to be based on the formation of an adequate internal mental model as a specific type of mental network. The learning process for such a mental model conceptualised as a mental network, is a form of (...

3D-PulCNN: Pulmonary cancer classification from hyperspectral images using convolution combination unit based CNN.

Journal of biophotonics
Pulmonary cancer is one of the most common malignancies worldwide. Accurate classification of its subtypes is required in differential diagnosis. However, existing algorithms are mostly based on color images, and the improvement of accuracy is quite ...