On the public citation graph

Augmented Adaptive Filter for Real-Time Sea State Estimation Using Vessel Motions Through Deep Learning

https://doi.org/10.1115/omae2023-104286

0 signed · 11 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4844900openalex-extracted

Part a: Innovative Data Analysis Approach to Enhance Machine Learning Efficiency for Seakeeping Purposes

inferred← citeshttps://doi.org/10.1016/j.oceaneng.2024.116701openalex-snapshot

Online short-term ship response prediction with dynamic buffer window using transient free switching filter

inferred← citeshttps://doi.org/10.1017/dce.2026.10073openalex-snapshot

Structural condition-based maintenance for naval vessels: an end-to-end perspective

inferred← citeshttps://doi.org/10.1109/joe.2025.3596359openalex-snapshot

Real-Time Wave Identification for Stationary Marine Units: A Deep Transfer Learning Approach With Adaptive Windowing

inferred← citeshttps://doi.org/10.21203/rs.3.rs-3826677/v1openalex-snapshot

Real-Time Sea State Estimation Using Deep Transfer Learning; an Integrated Framework

inferred← citeshttps://doi.org/10.21203/rs.3.rs-4463215/v1openalex-snapshot

Integrated Framework for Real-time Sea State Estimation of Stationary Marine Units Using Wave Buoy Analogy

inferred← citeshttps://doi.org/10.29007/2gnpopenalex-snapshot

Dynamic Windowing Algorithm to Improve Ship Response Prediction in Transitory Conditions

inferred← citeshttps://doi.org/10.3390/app15010158openalex-snapshot

Part A: Innovative Data Augmentation Approach to Enhance Machine Learning Efficiency—Case Study for Hydrodynamic Purposes

inferred← citeshttps://doi.org/10.3390/app15010346openalex-snapshot

Part B: Innovative Data Augmentation Approach to Boost Machine Learning for Hydrodynamic Purposes—Computational Efficiency

inferred← citeshttps://doi.org/10.3390/jmse12122312openalex-snapshot

An Integrated Framework for Real-Time Sea-State Estimation of Stationary Marine Units Using Wave Buoy Analogy

inferred← citeshttps://doi.org/10.3390/jmse13101919openalex-snapshot

A Low-Frequency Component Filtering Method for Heave Acceleration Signal of Marine Ship

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.