Nectar Track

• Disenchantment with Emotion Recognition Technologies: A Comparison Between Humans Observers and Automatic Classifiers
  Damien Dupré


• Persistence pays off: Paying Attention to What the LSTM Gating Mechanism Persists
  Giancarlo Salton and John Kelleher


• KalmanTune: A Kalman filter based tuning method to make boosted ensembles robust to class-label noise
  Arjun Pakrashi and Brian Mac Namee

Full Paper Track

• Active Learning for the Text Classification of Rock Climbing Logbook Data
  Eoghan Cunningham and Derek Greene


• TensorFlow enabled Deep Learning Model Optimization for enhanced Realtime Person Detection using Raspberry Pi operating at the Edge
  Reenu Mohandas, Mangolika Bhattacharya, Mihai Penica, Martin Hayes and Karl Van Camp


• Streetseek – Understanding Public Space Engagement Using Deep Learning & Thermal Imaging
  Ciarán O’Mara, Eoghan Mulcahy, John Nelson and Pepijn Van de Ven


• Differentiation in Personality Emotion Mappings From Self Reported Emotion and Automatically Classified Emotion
  Ryan Donovan, Ruairi O’Reilly and Aoife Johnson


• Geoff: A Linked Data Vocabulary for Describing the Form and Function of Spatial Objects
  Kristian McGlinn


• An Evacuation Route Model for Disaster Affected Areas
  Vinaysheel Kishor Wagh, Pramod Pathak, Paul Stynes and Luis Gustavo Nardin


• LightGWAS: A Novel Machine Learning Procedure for Genome-Wide Association Study
  Bruno Ambrozio, Luca Longo and Lucas Rizzo


• Exploring Composite Dataset Biases for Heart Sound Classification
  Davoud Shariat Panah, Andrew Hines and Susan Mckeever


• Using Navigable Small Worlds to Speed Up Time-Series Classification
  Vivek Mahato and Pádraig Cunningham


• Combining Local Search and Genetic Algorithm for Two-Dimensional Guillotine Bin Packing Problems with partial sequence constraint
  Filipe Souza and Diarmuid Grimes


• Incorporating Explainable Artificial Intelligence (XAI) to aid Understanding of Machine Learning in the Healthcare Domain
  Urja Pawar, Donna O’Shea, Susan Rea and Ruairi O’Reilly


• Exploring the potential of defeasible argumentation for quantitative inferences in real-world contexts: An assessment of computational trust
  Lucas Rizzo, Pierpaolo Dondio and Luca Longo


• A comparative analysis of rule-based, model-agnostic methods for explainable artificial intelligence
  Giulia Vilone, Luca Longo and Lucas Rizzo


• Finding Short Lived Events on Social Media
  David Kilroy, Simon Caton and Graham Healy


• Assessing the Appetite for Trustworthiness and the Regulation of Artificial Intelligence in Europe
  Labhaoise Nifhaolain, Andrew Hines and Vivek Nallur


• Where’s the Why? In Search of Chains of Causes for Query Events
  Suchana Datta, Derek Greene, Debasis Ganguly, Dwaipayan Roy and Mandar Mitra
  

Student Track

• Identifying Complaints from Product Reviews: A Case Study on Hindi
  Raghvendra Pratap Singh, Rejwanul Haque, Mohammed Hasanuzzaman and Andy Way


• Demand Prediction for Shared Mobility Services using Time Series Modelling
  Rudi Camilleri and Jeremy Debattista


• Optimising PID Control with Residual Policy Reinforcement Learning
  Andrew Hynes, Ivana Dusparic and Elena Sapozhnikova


• Synthesising Tabular Data using Wasserstein Conditional GANs with Gradient Penalty (WCGAN-GP)
  Manhar Singh Walia, Brendan Tierney and Susan Mckeever


• An Investigation of Transfer Learning for a Lifelog Dataset
  Tejal Nijai, Akanksha Rajpute and Graham Healy


• Neural Architecture Search using Particle Swarm and Ant Colony Optimization
  Seamus Lankford and Diarmuid Grime


• A Multi-class Approach – Building a Visual Classifier based on Textual Descriptions using Zero-Shot Learning
  Preeti Jagdish Sajjan and Frank G Glavin


• Less is More when Applying Transfer Learning to Multi-Spectral Data
  Yuvraj Sharma and Robert Ross


• Using GANs to Synthesise Minimum Training Data forDeepfake Generation
  Simranjeet Singh, Rajneesh Sharma and Alan Smeaton


• Intentional Forgetting: Investigating Interpretations and Future Potentials of Cognitive Control
  Alysha Higgins


• Analysis of Machine Learning Methods for Predicting Stock Prices
  Oluwadurotimi Onibonoje, Kevin Djoussa and Mark Roantree


• Improved Speech Synthesis using Generative Adversarial Networks
  Dineshraj Gunasekaran, Gautham Venkatraj, Eoin Brophy and Tomas Ward


• Simple Question Answering Over a Domain-Specific Knowledge Graph using BERT by Transfer Learning
  Mani Vegupatti, Matthias Nickles and Bharathi Raja Chakravarthi