Publications for Problem Identification¶

This page lists research publications that have utilized the DroneNLP Problem Identification or are directly related to the task of identifying problem-indicating records and its severity in the drone flight logs messages.

DroPTC: Sentence-level drone flight log forensics using contrastive learning and explainable AI¶

Swardiantara Silalahi, Tohari Ahmad, Hudan Studiawan*, Frank Breitinger
DFRWS EU, 2026 DOI Code

Dataset for drone problem identification and severity estimation¶

Swardiantara Silalahi, Tohari Ahmad*, Hudan Studiawan
Data in Brief, 2026 DOI Data

Interpretable Ordinal-Aware With Contrastive-Enhanced Anomaly Severity Detection on UAV Flight Log Messages¶

Swardiantara Silalahi, Tohari Ahmad*, Hudan Studiawan, Eirini Anthi, Lowri Williams
IEEE Access, 2025 DOI Code

Severity-Oriented Multiclass Drone Flight Logs Anomaly Detection¶

Swardiantara Silalahi, Tohari Ahmad*, Hudan Studiawan, Eirini Anthi, Lowri Williams
IEEE Access, 2024 DOI Code

Drone Flight Log Anomaly Severity Classification via Sentence Embedding¶

Swardiantara Silalahi, Tohari Ahmad*, Hudan Studiawan
ICoABCD, 2023 DOI

Transformer-based Sentiment Analysis for Anomaly Detection on Drone Forensic Timeline¶

Swardiantara Silalahi, Tohari Ahmad*, Hudan Studiawan
ISDFS, 2023 DOI Code