Explainable Artificial Intelligence
Second World Conference, xAI 2024, Valletta, Malta, July 17–19, 2024, Proceedings, Part II
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Article
Open AccessFractal dimensions and machine learning for detection of Parkinson’s disease in resting-state electroencephalography
Parkinson’s disease (PD) is an incurable neurological disorder that degenerates the cerebrospinal nervous system and hinders motor functions. Electroencephalography (EEG) signal analysis can provide reliable i...
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Book and Conference Proceedings
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Chapter and Conference Paper
CNN-Based Explanation Ensembling for Dataset, Representation and Explanations Evaluation
Explainable Artificial Intelligence has gained significant attention due to the widespread use of complex deep learning models in high-stake domains such as medicine, finance, and autonomous cars. However, dif...
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Book and Conference Proceedings
Explainable Artificial Intelligence
Second World Conference, xAI 2024, Valletta, Malta, July 17–19, 2024, Proceedings, Part III
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Chapter and Conference Paper
A Comparative Analysis of SHAP, LIME, ANCHORS, and DICE for Interpreting a Dense Neural Network in Credit Card Fraud Detection
Financial institutions heavily rely on advanced Machine Learning algorithms to screen transactions. However, they face increasing pressure from regulators and the public to ensure AI accountability and transpa...
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Book and Conference Proceedings
Explainable Artificial Intelligence
Second World Conference, xAI 2024, Valletta, Malta, July 17–19, 2024, Proceedings, Part I
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Book and Conference Proceedings
Explainable Artificial Intelligence
Second World Conference, xAI 2024, Valletta, Malta, July 17–19, 2024, Proceedings, Part IV
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Chapter and Conference Paper
SRFAMap: A Method for Map** Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps
Many explainable AI methods for generating medical image saliency maps exist, but most are devoted to working on trained neural network-based models. At the same time, many medical image classification neural ...
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Chapter and Conference Paper
Correction to: Explainable Artificial Intelligence
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Chapter and Conference Paper
Selecting Textural Characteristics of Chest X-Rays for Pneumonia Lesions Classification with the Integrated Gradients XAI Attribution Method
Global texture characteristics are powerful tools for solving medical image classification tasks. There are many such characteristics like Grey-Level Co-occurrence Matrices, Grey-Level Run-Length Matrices, Gre...
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Chapter and Conference Paper
Investigating the Effect of Pre-processing Methods on Model Decision-Making in EEG-Based Person Identification
Electroencephalography (EEG) data has emerged as a promising modality for biometric applications, offering unique and secure personal identification and authentication methods. This research comprehensively co...
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Book and Conference Proceedings
Artificial Intelligence and Cognitive Science
30th Irish Conference, AICS 2022, Munster, Ireland, December 8–9, 2022, Revised Selected Papers
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Chapter and Conference Paper
An Exploration of the Latent Space of a Convolutional Variational Autoencoder for the Generation of Musical Instrument Tones
Variational Autoencoders (VAEs) constitute one of the most significant deep generative models for the creation of synthetic samples. In the field of audio synthesis, VAEs have been widely used for the generati...
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Book and Conference Proceedings
Explainable Artificial Intelligence
First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part III
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Book and Conference Proceedings
Explainable Artificial Intelligence
First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part II
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Book and Conference Proceedings
Explainable Artificial Intelligence
First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part I
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Chapter and Conference Paper
Development of a Human-Centred Psychometric Test for the Evaluation of Explanations Produced by XAI Methods
One goal of Explainable Artificial Intelligence (XAI) is to interpret and explain the inferential process of data-driven machine-learned models to make it comprehensible for humans. To reach it, it is necessar...
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Chapter and Conference Paper
An Ontological Approach for Recommending a Feature Selection Algorithm
Feature selection plays an important role in machine learning or data mining problems. Removing irrelevant features increases model accuracy and reduces the computational cost. However, selecting important fea...
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Chapter and Conference Paper
A Survey on the Application of Virtual Reality in Event-Related Potential Research
Virtual reality (VR) is getting traction in many contexts, allowing users to have a real-life experience in a virtual world. However, its application in the field of Neuroscience, and above all probing newer a...
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Chapter and Conference Paper
Data Quality Assessment of Comma Separated Values Using Linked Data Approach
With an increasing amount of structured data on the web, the need to understand and convert it into linked data is growing. One of the most frequent data formats is Comma Separated Value (CSV). However, it is ...
