| Description |
1 online resource (406 p.) |
| Series |
Frontiers in Artificial Intelligence and Applications Series ; v.375 |
|
Frontiers in artificial intelligence and applications.
|
| Contents |
Intro -- Title Page -- Preface -- About the Conference -- Contents -- Part 1. Invited Talks -- Unlocking the Power of LLMs: Navigating Challenges for Industry in the AI Renaissance -- Formalization of Drug Dose Titration Procedures -- Part 2. Machine Learning: Theory and Applications -- Inter-Satellite Link Prediction with Supervised Learning Based on Kepler and SGP4 Orbits -- Hydranet: A Neural Network for the Estimation of Multi-Valued Treatment Effects -- Applying Generative Models and Transfer Learning to Physiological Data Classification |
|
Stacking Up for Success: A Cascade Network Model for Efficient Road Crack Segmentation -- Internal Representation and Shepard's Law in an Artificial Haptic System -- Expert Finding for Citizen Science -- Clustering of Qualitative Time Series for 3D Printing Quality Management -- Cognitive Similarity Through Bibliometric Analysis -- Full-Range Yaw Prediction: A Multi-View Approach for 3D Head Model Pose Estimation Using Convolutional Neural Networks -- A Deep Learning-Based Pipeline for Computing Brain Biomarkers from MRI |
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Identifying Patterns Between Acoustic Environment and Visual Landscape Through Semantic Segmentation Based on Deep Learning -- OPNet: A One-Shot Image Similarity Algorithm for Production Systems -- Analyzing Car Configurator Impact Through Genetic Algorithm from a Regional Perspective -- Navigating Black Swan Events in Algorithmic Trading: A Reinforcement Learning Perspective -- Machine Learning in Particle Physics Experiments: The Case of LHCb -- Petri-Nets-Based Controllers Generation Using Genetic Programming -- Addressing Scale and Density Challenges in LiDAR Point Classification |
|
A Bayesian Network Framework to Study Class Noise: Exploring the Filtering of Completely Random Noise -- EduSign: Real-Time Application for Spanish Sign Language Recognition -- Automated Cleanliness Scoring and Digestive Content Segmentation for Capsule Endoscopy -- Development of an Automated CBCT Nerve and Teeth Segmentation Tool Based on Deep Learning -- Zero-Shot Prediction for Emotion Recognition Using Deep Spectrum Features -- Part 3. AI for Health: Theory and Applications |
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Bayesian Optimization with Additive Kernels for the Calibration of Simulation Models to Perform Cost-Effectiveness Analysis -- Exploring the Role of Explainability in AI-Assisted Embryo Selection -- Longitudinal Segmentation of Multiple Sclerosis Lesions Using nnU-Net Architecture -- Resource Allocation in Home Care Services Using Reinforcement Learning -- Assessing VTE Risk in Cancer Patients Using Deep Learning Synthetic Data Generation and Domain Adaptation Techniques |
| Notes |
Description based upon print version of record |
|
Hipertension Demand Forecasting Using Cross-Correlation and Lagged Multiple Linear Regression Models for Anticipating Health Resources Needs |
| Genre/Form |
Electronic books
|
| Form |
Electronic book
|
| Author |
Ros, R
|
|
Nin, J
|
| ISBN |
9781643684499 |
|
1643684493 |
|
