AIMC Topic: Neural Networks, Computer

Clear Filters Showing 16711 to 16720 of 31376 articles

Deep learning-based mixed-dimensional Gaussian mixture model for characterizing variability in cryo-EM.

Nature methods
Structural flexibility and/or dynamic interactions with other molecules is a critical aspect of protein function. Cryogenic electron microscopy (cryo-EM) provides direct visualization of individual macromolecules sampling different conformational and...

Attention-Based Multi-Scale Convolutional Neural Network (A+MCNN) for Multi-Class Classification in Road Images.

Sensors (Basel, Switzerland)
Automated pavement distress recognition is a key step in smart infrastructure assessment. Advances in deep learning and computer vision have improved the automated recognition of pavement distresses in road surface images. This task remains challengi...

Affective Computing on Machine Learning-Based Emotion Recognition Using a Self-Made EEG Device.

Sensors (Basel, Switzerland)
In this research, we develop an affective computing method based on machine learning for emotion recognition using a wireless protocol and a wearable electroencephalography (EEG) custom-designed device. The system collects EEG signals using an eight-...

Multi-Sensor Context-Aware Based Chatbot Model: An Application of Humanoid Companion Robot.

Sensors (Basel, Switzerland)
In aspect of the natural language processing field, previous studies have generally analyzed sound signals and provided related responses. However, in various conversation scenarios, image information is still vital. Without the image information, mi...

Estimation of Stroke Volume Variance from Arterial Blood Pressure: Using a 1-D Convolutional Neural Network.

Sensors (Basel, Switzerland)
BACKGROUND: We aimed to create a novel model using a deep learning method to estimate stroke volume variation (SVV), a widely used predictor of fluid responsiveness, from arterial blood pressure waveform (ABPW).

MSF-Net: Multi-Scale Feature Learning Network for Classification of Surface Defects of Multifarious Sizes.

Sensors (Basel, Switzerland)
In the field of surface defect detection, the scale difference of product surface defects is often huge. The existing defect detection methods based on Convolutional Neural Networks (CNNs) are more inclined to express macro and abstract features, and...

Interrogating theoretical models of neural computation with emergent property inference.

eLife
A cornerstone of theoretical neuroscience is the circuit model: a system of equations that captures a hypothesized neural mechanism. Such models are valuable when they give rise to an experimentally observed phenomenon -- whether behavioral or a patt...

A Defect Detection Method for Rail Surface and Fasteners Based on Deep Convolutional Neural Network.

Computational intelligence and neuroscience
As a result of long-term pressure from train operations and direct exposure to the natural environment, rails, fasteners, and other components of railway track lines inevitably produce defects, which have a direct impact on the safety of train operat...

Human-in-the-Loop Predictive Analytics Using Statistical Learning.

Journal of healthcare engineering
The human-in-the-loop cyber-physical system provides numerous solutions for the challenges faced by the doctors or medical practitioners. There is a linear trend of advancement and automation in the medical field for the early diagnosis of several di...

Decision-Making Model of Product Modeling Big Data Design Scheme Based on Neural Network Optimized by Genetic Algorithm.

Computational intelligence and neuroscience
At present, machine learning artificial neural network technology, as one of the core technologies of enterprises, has received unprecedented attention. This technology is widely used in automatic driving, pattern recognition, teaching aid, product m...