12 citations · 20 across the 8 of their papers we have counts for
8 papers
Classification of Operational Records in Aviation Using Deep Learning Approaches
Aziida Nanyonga, Graham Wild
Ensuring safety in the aviation industry is critical, even minor anomalies can lead to severe consequences. This study evaluates the performance of four different models for DP (de…
Phase of Flight Classification in Aviation Safety using LSTM, GRU, and BiLSTM: A Case Study with ASN Dataset
Aziida Nanyonga, Hassan Wasswa, Graham Wild
Safety is the main concern in the aviation industry, where even minor operational issues can lead to serious consequences. This study addresses the need for comprehensive aviation…
Exploring Aviation Incident Narratives Using Topic Modeling and Clustering Techniques
Aziida Nanyonga, Hassan Wasswa, Ugur Turhan +2
Aviation safety is a global concern, requiring detailed investigations into incidents to understand contributing factors comprehensively. This study uses the National Transportatio…
Aviation Safety Enhancement via NLP & Deep Learning: Classifying Flight Phases in ATSB Safety Reports
Aziida Nanyonga, Hassan Wasswa, Graham Wild
Aviation safety is paramount, demanding precise analysis of safety occurrences during different flight phases. This study employs Natural Language Processing (NLP) and Deep Learnin…
Applications of natural language processing in aviation safety: A review and qualitative analysis
Aziida Nanyonga, Keith Joiner, Ugur Turhan +1
This study explores using Natural Language Processing in aviation safety, focusing on machine learning algorithms to enhance safety measures. There are currently May 2024, 34 Scopu…
Comparative Study of Deep Learning Architectures for Textual Damage Level Classification
Aziida Nanyonga, Hassan Wasswa, Graham Wild
Given the paramount importance of safety in the aviation industry, even minor operational anomalies can have significant consequences. Comprehensive documentation of incidents and…