AIMC Topic: Neural Networks, Computer

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A Deep Learning Framework About Traffic Flow Forecasting for Urban Traffic Emission Monitoring System.

Frontiers in public health
As urban traffic pollution continues to increase, there is an urgent need to build traffic emission monitoring and forecasting system for the urban traffic construction. The traffic emission monitoring and forecasting system's core is the prediction ...

Analysis of random synchronization under bilayer derivative and nonlinear delay networks of neuron nodes via fixed time policies.

ISA transactions
In order to solve a challenging problem, i.e., fixed time synchronization of bilayer networks with derivative coupling and nonlinear delay coupling, fixed time polices are brought to achieve random synchronization for bilayer multiple weight hybrid c...

MDReg-Net: Multi-resolution diffeomorphic image registration using fully convolutional networks with deep self-supervision.

Human brain mapping
We present a diffeomorphic image registration algorithm to learn spatial transformations between pairs of images to be registered using fully convolutional networks (FCNs) under a self-supervised learning setting. Particularly, a deep neural network ...

Low-degree term first in ResNet, its variants and the whole neural network family.

Neural networks : the official journal of the International Neural Network Society
To explain the working mechanism of ResNet and its variants, this paper proposes a novel argument of shallow subnetwork first (SSF), essentially low-degree term first (LDTF), which also applies to the whole neural network family. A neural network wit...

Real-time image-based air quality estimation by deep learning neural networks.

Journal of environmental management
Air quality profoundly impacts public health and environmental equity. Efficient and inexpensive air quality monitoring instruments could be greatly beneficial for human health and air pollution control. This study proposes an image-based deep learni...

MAFF-Net: Multi-Attention Guided Feature Fusion Network for Change Detection in Remote Sensing Images.

Sensors (Basel, Switzerland)
One of the most important tasks in remote sensing image analysis is remote sensing image Change Detection (CD), and CD is the key to helping people obtain more accurate information about changes on the Earth's surface. A Multi-Attention Guided Featur...

A gradient-based automatic optimization CNN framework for EEG state recognition.

Journal of neural engineering
. The electroencephalogram (EEG) signal, as a data carrier that can contain a large amount of information about the human brain in different states, is one of the most widely used metrics for assessing human psychophysiological states. Among a variet...

Deep learning model inspired by lateral line system for underwater object detection.

Bioinspiration & biomimetics
Inspired by the lateral line systems of various aquatic organisms that are capable of hydrodynamic imaging using ambient flow information, this study develops a deep learning-based object localization model that can detect the location of objects usi...

Museum Relic Image Detection and Recognition Based on Deep Learning.

Computational intelligence and neuroscience
To improve the accuracy of museum cultural relic image recognition, the DenseNet and ResNet are selected as the backbone neural networks for detection and recognition. In view of the small target problem in cultural relics, the feature pyramid is int...

Research on the Communication Strategy of History and Culture in Shaanxi Based on BP Neural Network Model.

Computational intelligence and neuroscience
Shaanxi is one of China's most important cradles of civilization. The main vein of Chinese culture is rich history and culture, and brilliant red culture embodies the essence of socialist core values. It is still relatively weak to deeply analyze the...