AICS 2020

List of Accepted Papers

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

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Technological University Dublin, Republic of Ireland