Imagen de Portada

Towards Explainable Deep Learning for Ship Trajectory Prediction in Inland Waterways

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Legel, Tom, Söffker, Dirk, Schätzle, Roland, Donandt, Kathrin
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Incorporating Navigation Context into Inland Vessel Trajectory Prediction: A Gaussian Mixture Model and Transformer Approach
por: Donandt, Kathrin, et al.
Publicado: (2024)

Short-term Inland Vessel Trajectory Prediction with Encoder-Decoder Models
por: Donandt, Kathrin, et al.
Publicado: (2024)

Spatial and social situation-aware transformer-based trajectory prediction of autonomous systems
por: Donandt, Kathrin, et al.
Publicado: (2024)

Improved context-sensitive transformer model for inland vessel trajectory prediction
por: Donandt, Kathrin, et al.
Publicado: (2024)

Reliability comparison of vessel trajectory prediction models via Probability of Detection
por: Rastin, Zahra, et al.
Publicado: (2025)

Advanced POD-Based Performance Evaluation of Classifiers Applied to Human Driver Lane Changing Prediction
por: Rastin, Zahra, et al.
Publicado: (2024)

2-Level Reinforcement Learning for Ships on Inland Waterways: Path Planning and Following
por: Waltz, Martin, et al.
Publicado: (2023)

Architecture for Trajectory-Based Fishing Ship Classification with AIS Data
por: Pedroche, David Sánchez, et al.
Publicado: (2025)

Combining Deep Learning and Explainable AI for Toxicity Prediction of Chemical Compounds
por: Popescu, Eduard, et al.
Publicado: (2025)

Predicting Barge Tow Size on Inland Waterways Using Vessel Trajectory Derived Features: Proof of Concept
por: Agorku, Geoffery, et al.
Publicado: (2025)

Causally-informed Deep Learning towards Explainable and Generalizable Outcomes Prediction in Critical Care
por: Cheng, Yuxiao, et al.
Publicado: (2025)

Exploring Machine Learning, Deep Learning, and Explainable AI Methods for Seasonal Precipitation Prediction in South America
por: Domingos, Matheus Corrêa, et al.
Publicado: (2025)

Towards Explainable Traffic Flow Prediction with Large Language Models
por: Guo, Xusen, et al.
Publicado: (2024)

A Survey on Explainable Deep Reinforcement Learning
por: Cheng, Zelei, et al.
Publicado: (2025)

DPD-Cancer: Explainable Graph-Based Deep Learning for Small Molecule Anti-Cancer Activity Prediction
por: Strømme, Magnus H., et al.
Publicado: (2026)

Explainable Machine Learning for ICU Readmission Prediction
por: de Sá, Alex G. C., et al.
Publicado: (2023)

Evaluating Robustness of Reinforcement Learning Algorithms for Autonomous Shipping
por: Lesy, Bavo, et al.
Publicado: (2024)

Abstracted Trajectory Visualization for Explainability in Reinforcement Learning
por: Takagi, Yoshiki, et al.
Publicado: (2024)

Intrinsic Explainability of Multimodal Learning for Crop Yield Prediction
por: Najjar, Hiba, et al.
Publicado: (2025)

Using Part-based Representations for Explainable Deep Reinforcement Learning
por: Kirtas, Manos, et al.
Publicado: (2024)

Generative AI in Ship Design
por: Thakur, Sahil, et al.
Publicado: (2024)

Towards Explainable Fusion and Balanced Learning in Multimodal Sentiment Analysis
por: Luo, Miaosen, et al.
Publicado: (2025)

AIS-LLM: A Unified Framework for Maritime Trajectory Prediction, Anomaly Detection, and Collision Risk Assessment with Explainable Forecasting
por: Park, Hyobin, et al.
Publicado: (2025)

Towards Reproducibility in Predictive Process Mining: SPICE -- A Deep Learning Library
por: Stritzel, Oliver, et al.
Publicado: (2025)

Towards Personalised Patient Risk Prediction Using Temporal Hospital Data Trajectories
por: Barnes, Thea, et al.
Publicado: (2024)

Towards Transparent and Accurate Diabetes Prediction Using Machine Learning and Explainable Artificial Intelligence
por: Khokhar, Pir Bakhsh, et al.
Publicado: (2025)

MSD-LLM: Predicting Ship Detention in Port State Control Inspections with Large Language Model
por: Jin, Jiongchao, et al.
Publicado: (2025)

Evaluating Explainability in Machine Learning Predictions through Explainer-Agnostic Metrics
por: Munoz, Cristian, et al.
Publicado: (2023)

Enhancing Psychologists' Understanding through Explainable Deep Learning Framework for ADHD Diagnosis
por: Rehman, Abdul, et al.
Publicado: (2026)

Explainable Hierarchical Deep Learning Neural Networks (Ex-HiDeNN)
por: Batley, Reza T., et al.
Publicado: (2025)

Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning
por: Luo, Kang, et al.
Publicado: (2024)

An Explainable Ensemble Learning Framework for Crop Classification with Optimized Feature Pyramids and Deep Networks
por: Masud, Syed Rayhan, et al.
Publicado: (2026)

Clarifying Model Transparency: Interpretability versus Explainability in Deep Learning with MNIST and IMDB Examples
por: Raj, Mitali
Publicado: (2025)

Co-Activation Graph Analysis of Safety-Verified and Explainable Deep Reinforcement Learning Policies
por: Gross, Dennis, et al.
Publicado: (2025)

Predicting Barge Presence and Quantity on Inland Waterways using Vessel Tracking Data: A Machine Learning Approach
por: Agorku, Geoffery, et al.
Publicado: (2024)

Policy Induction: Predicting Startup Success via Explainable Memory-Augmented In-Context Learning
por: Mu, Xianling, et al.
Publicado: (2025)

Generalizable Trajectory Prediction via Inverse Reinforcement Learning with Mamba-Graph Architecture
por: Li, Wenyun, et al.
Publicado: (2025)

SkillTree: Explainable Skill-Based Deep Reinforcement Learning for Long-Horizon Control Tasks
por: Wen, Yongyan, et al.
Publicado: (2024)

Compressing Deep Neural Networks Using Explainable AI
por: Soroush, Kimia, et al.
Publicado: (2025)

Towards Interpretable End-Stage Renal Disease (ESRD) Prediction: Utilizing Administrative Claims Data with Explainable AI Techniques
por: Li, Yubo, et al.
Publicado: (2024)