Outputs (104)

Accelerated pattern search with variable solution size for simultaneous instance selection and generation (2022)
Presentation / Conference Contribution
Le, H. L., Neri, F., Landa-Silva, D., & Triguero, I. (2022, July). Accelerated pattern search with variable solution size for simultaneous instance selection and generation. Poster presented at Genetic and Evolutionary Computation Conference Companion (GECCO 2022), Boston, USA and online

The search for the optimum in a mixed continuous-combinatorial space is a challenging task since it requires operators that handle both natures of the search domain. Instance reduction (IR), an important pre-processing technique in data science, is o... Read More about Accelerated pattern search with variable solution size for simultaneous instance selection and generation.

Many-objective test case generation for graphical user interface applications via search-based and model-based testing (2022)
Journal Article
de Santiago, V. A., Özcan, E., & Balera, J. M. (2022). Many-objective test case generation for graphical user interface applications via search-based and model-based testing. Expert Systems with Applications, 208, Article 118075. https://doi.org/10.1016/j.eswa.2022.118075

The majority of the studies that generate test cases for graphical user interface (GUI) applications are based on or address functional requirements only. In spite of the fact that interesting approaches have been proposed, they do not address functi... Read More about Many-objective test case generation for graphical user interface applications via search-based and model-based testing.

An Improved Ant Colony Approach for the Competitive Traveling Salesmen Problem (2022)
Presentation / Conference Contribution
Du, X., Bai, R., Cui, T., Qu, R., & Li, J. (2022, July). An Improved Ant Colony Approach for the Competitive Traveling Salesmen Problem. Presented at 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings, Padua, Italy

A competitive traveling salesmen problem is a variant of traveling salesman problem in that multiple agents compete with each other in visiting a number of cities. The agent who is the first one to visit a city will receive a reward. Each agent aims... Read More about An Improved Ant Colony Approach for the Competitive Traveling Salesmen Problem.

Counterfactual rule generation for fuzzy rule-based classification systems (2022)
Presentation / Conference Contribution
Zhang, T., Wagner, C., & Garibaldi, J. M. (2022, July). Counterfactual rule generation for fuzzy rule-based classification systems. Presented at 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Padua, Italy

EXplainable Artificial Intelligence (XAI) is of in-creasing importance as researchers and practitioners seek better transparency and verifiability of AI systems. Mamdani fuzzy systems can provide explanations based on their linguistic rules, and thus... Read More about Counterfactual rule generation for fuzzy rule-based classification systems.

Visualization of Interval Regression for Facilitating Data and Model Insight (2022)
Presentation / Conference Contribution
Kabir, S., & Wagner, C. (2022, July). Visualization of Interval Regression for Facilitating Data and Model Insight. Presented at IEEE World Congress on Computational Intelligence 2022 (IEEE WCCI 2022), Padova, Italy

With growing significance of interval-valued data, interest in artificial intelligence methods tailored to this data type is similarly increasing across a range of application domains. Here, regression, i.e., the modelling of the association between... Read More about Visualization of Interval Regression for Facilitating Data and Model Insight.

Does Permitting Uncertain Estimates Help or Hinder the Wisdom of Crowds? (2022)
Presentation / Conference Contribution
Ellerby, Z., & Wagner, C. (2022, July). Does Permitting Uncertain Estimates Help or Hinder the Wisdom of Crowds?. Presented at 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Padua, Italy

This paper adds to a growing body of research into the practical utility of using interval-valued (IV) response modes to efficiently capture richer quantitative data from people-e.g., through surveys. Specifically, IV responses offer a cohesive metho... Read More about Does Permitting Uncertain Estimates Help or Hinder the Wisdom of Crowds?.

Quality Quantification in Deep Convolutional Neural Networks for Skin Lesion Segmentation using Fuzzy Uncertainty Measurement (2022)
Presentation / Conference Contribution
Lin, Q., Chen, X., Chen, C., & Garibaldi, J. M. (2022, July). Quality Quantification in Deep Convolutional Neural Networks for Skin Lesion Segmentation using Fuzzy Uncertainty Measurement. Presented at 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Padua, Italy

Deep convolutional neural networks (DCNN)-based methods have achieved promising performance in semantic image segmentation. However, in practical applications, it is important not only to produce the segmentation result but also to inform the segment... Read More about Quality Quantification in Deep Convolutional Neural Networks for Skin Lesion Segmentation using Fuzzy Uncertainty Measurement.

Nigeria’s Digital Identification (ID) Management Program: Ethical, Legal and Socio-Cultural concerns (2022)
Journal Article
Eke, D., Oloyede, R., Ochang, P., Borokini, F., Adeyeye, M., Sorbarikor, L., Wale-Oshinowo, B., & Akintoye, S. (2022). Nigeria’s Digital Identification (ID) Management Program: Ethical, Legal and Socio-Cultural concerns. Journal of Responsible Technology, 11, 100039. https://doi.org/10.1016/j.jrt.2022.100039

National digital identity management systems have gained traction as a critical tool for inclusion of citizens in the increasingly digitised public services. With the help of the World Bank, countries around the world are committing to building and p... Read More about Nigeria’s Digital Identification (ID) Management Program: Ethical, Legal and Socio-Cultural concerns.

Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles (2022)
Data
Brocklehurst, C., & Radenkovic, M. (2022). Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles. [Data]. https://doi.org/10.3390/jsan11030035

The increased interest in autonomous vehicles has led to the development of novel networking protocols in VANETs In such a widespread safety-critical application, security is paramount to the implementation of the networks. We view new autonomous veh... Read More about Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles.

LMISA: A Lightweight Multi-modality Image Segmentation Network via Domain Adaptation using Gradient Magnitude and Shape Constraint (2022)
Journal Article
Jafari, M., Francis, S., Garibaldi, J. M., & Chen, X. (2022). LMISA: A Lightweight Multi-modality Image Segmentation Network via Domain Adaptation using Gradient Magnitude and Shape Constraint. Medical Image Analysis, 81, Article 102536. https://doi.org/10.1016/j.media.2022.102536

In medical image segmentation, supervised machine learning models trained using one image modality (e.g. computed tomography (CT)) are often prone to failure when applied to another image modality (e.g. magnetic resonance imaging (MRI)) even for the... Read More about LMISA: A Lightweight Multi-modality Image Segmentation Network via Domain Adaptation using Gradient Magnitude and Shape Constraint.