IEEE

Integrated Graphical Representation of Highway Scenarios to Improve Trajectory Prediction of Surrounding Vehicles

Abstract: Varying numbers and types of vehicles, various road structures and traffic rules bring difficulties to an autonomous vehicle driving in highway traffic scenarios. It is important to ...
GitHub

pyClim-SDM: Statistical Downscaling for Climate Change Projections with a Graphical User Interface

Citation: Hernanz, A., Correa, C., García-Valero, J. A., Domínguez, M., Rodríguez-Guisado, E., & Rodríguez-Camino, E. (2023). pyClim-SDM: Service for generation ...
Scientific Research Publishing

Advanced Skin Disease Diagnosis and Treatment: Leveraging Convolutional Neural Networks for Image-Based Prediction and Comprehensive Health Assistance ()

Skin conditions are a worldwide health issue that requires prompt and accurate diagnosis in order to be effectively treated. This study presents a Convolutional Neural Network (CNN)-based automated ...
Scientific Research Publishing

Multi-Head Attention Spatial-Temporal Graph Neural Networks for Traffic Forecasting ()

Accurate traffic prediction is crucial for an intelligent traffic system (ITS). However, the excessive non-linearity and complexity of the spatial-temporal correlation in traffic flow severely limit ...
Frontiers

Convolutional neural network (CNN)-enabled electrocardiogram (ECG) analysis: a comparison between standard twelve-lead and single-lead setups

Artificial intelligence (AI) has shown promise in the early detection of various cardiac conditions from a standard 12-lead electrocardiogram (ECG). However, the ability of AI to identify ...
UCL

Gatsby Bridging Programme

An intensive, fast-paced summer school for predoctoral students to build mathematical intuitions and skills necessary to enter the fields of theoretical neuroscience and foundational machine learning ...
C&EN

Improved Prediction Model of Protein and Peptide Toxicity by Integrating Channel Attention into a Convolutional Neural Network and Gated Recurrent Units

Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei 106, Taiwan Research Center for Artificial Intelligence in Medicine, Taipei ...
Frontiers

Convolutional Neural Networks Enable Robust Automatic Segmentation of the Rat Hippocampus in MRI After Traumatic Brain Injury

Registration-based methods are commonly used in the automatic segmentation of magnetic resonance (MR) brain images. However, these methods are not robust to the presence of gross pathologies that can ...
Europe PMC

Healthy Kidney Segmentation in the Dce-Mr Images Using a Convolutional Neural Network and Temporal Signal Characteristics.

Quantification of renal perfusion based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) requires determination of signal intensity time courses in the region of renal parenchyma.
C&EN

Quantification of Analyte Concentration in the Single Molecule Regime Using Convolutional Neural Networks

Single molecule (SM) detection represents the ultimate limit of chemical detection. Over the years, many experimental techniques have emerged with this capacity. Yet, SM detection and imaging methods ...