AIMC Topic: Spatio-Temporal Analysis
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Shaping dynamical neural computations using spatiotemporal constraints.
Biochemical and biophysical research communications
Jun 25, 2024
Dynamics play a critical role in computation. The principled evolution of states over time enables both biological and artificial networks to represent and integrate information to make decisions. In the past few decades, significant multidisciplinar...
Automated diagnosis of schizophrenia based on spatial-temporal residual graph convolutional network.
Biomedical engineering online
Jun 17, 2024
BACKGROUND: Schizophrenia (SZ), a psychiatric disorder for which there is no precise diagnosis, has had a serious impact on the quality of human life and social activities for many years. Therefore, an advanced approach for accurate treatment is requ...
Local spatiotemporal dynamics of particulate matter and oak pollen measured by machine learning aided optical particle counters.
The Science of the total environment
May 25, 2024
Conventional techniques for monitoring pollen currently have significant limitations in terms of labour, cost and the spatiotemporal resolution that can be achieved. Pollen monitoring networks across the world are generally sparse and are not able to...
Impact Exploration of Spatiotemporal Feature Derivation and Selection on Machine Learning-Based Predictive Models for Post-Embolization Cerebral Aneurysm Recanalization.
Cardiovascular engineering and technology
May 23, 2024
PURPOSE: To enhance the performance of machine learning (ML) models for the post-embolization recanalization of cerebral aneurysms, we evaluated the impact of hemodynamic feature derivation and selection method on six ML algorithms.
Local spatial and temporal relation discovery model based on attention mechanism for traffic forecasting.
Neural networks : the official journal of the International Neural Network Society
May 6, 2024
Recognizing the evolution pattern of traffic condition and making accurate prediction play a vital role in intelligent transportation systems (ITS). With the massive increase of available traffic data, deep learning-based models have attracted consid...
Spatiotemporal models of dengue epidemiology in the Philippines: Integrating remote sensing and interpretable machine learning.
Acta tropica
May 1, 2024
Previous dengue epidemiological analyses have been limited in spatiotemporal extent or covariate dimensions, the latter neglecting the multifactorial nature of dengue. These constraints, caused by rigid and traditional statistical tools which collaps...
Learning spatio-temporal patterns with Neural Cellular Automata.
PLoS computational biology
Apr 26, 2024
Neural Cellular Automata (NCA) are a powerful combination of machine learning and mechanistic modelling. We train NCA to learn complex dynamics from time series of images and Partial Differential Equation (PDE) trajectories. Our method is designed to...
High-spatial resolution ground-level ozone in Yunnan, China: A spatiotemporal estimation based on comparative analyses of machine learning models.
Environmental research
Mar 3, 2024
Monitoring ground-level ozone concentrations is a critical aspect of atmospheric environmental studies. Given the existing limitations of satellite data products, especially the lack of ground-level ozone characterization, and the discontinuity of gr...
Evaluating long-term and high spatiotemporal resolution of wet-bulb globe temperature through land-use based machine learning model.
Journal of exposure science & environmental epidemiology
Dec 16, 2023
BACKGROUND: The increase in global temperature and urban warming has led to the exacerbation of heatwaves, which negatively affect human health and cause long-term loss of work productivity. Therefore, a global assessment in temperature variation is ...
Investigation of spatiotemporal distribution and formation mechanisms of ozone pollution in eastern Chinese cities applying convolutional neural network.
Journal of environmental sciences (China)
Sep 11, 2023
Severe ground-level ozone (O) pollution over major Chinese cities has become one of the most challenging problems, which have deleterious effects on human health and the sustainability of society. This study explored the spatiotemporal distribution c...
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