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A pattern-based algorithm with fuzzy logic bin selector for online bin packing problem (2024)
Journal Article
Lin, B., Li, J., Cui, T., Jin, H., Bai, R., Qu, R., & Garibaldi, J. (2024). A pattern-based algorithm with fuzzy logic bin selector for online bin packing problem. Expert Systems with Applications, 249, Article 123515. https://doi.org/10.1016/j.eswa.2024.123515

The online bin packing problem is a well-known optimization challenge that finds application in a wide range of real-world scenarios. In the paper, we propose a novel algorithm called FuzzyPatternPack(FPP), which leverages fuzzy inference and pattern... Read More about A pattern-based algorithm with fuzzy logic bin selector for online bin packing problem.

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.

FuzzyDCNN: Incorporating Fuzzy Integral Layers to Deep Convolutional Neural Networks for Image Segmentation (2021)
Conference Proceeding
Lin, Q., Chen, X., Chen, C., & Garibaldi, J. M. (2021). FuzzyDCNN: Incorporating Fuzzy Integral Layers to Deep Convolutional Neural Networks for Image Segmentation. In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/fuzz45933.2021.9494456

Convolutional neural networks (CNNs) have achieved the state-of-the-art performance in many application areas, due to the capability of automatically extracting and aggregating spatial and channel-wise features from images. Most recent studies have c... Read More about FuzzyDCNN: Incorporating Fuzzy Integral Layers to Deep Convolutional Neural Networks for Image Segmentation.

An Extension of the FuzzyR Toolbox for Non-Singleton Fuzzy Logic Systems (2021)
Conference Proceeding
Chen, C., Zhao, Y., Wagner, C., Pekaslan, D., & Garibaldi, J. M. (2021). An Extension of the FuzzyR Toolbox for Non-Singleton Fuzzy Logic Systems. In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/fuzz45933.2021.9494472

Recent years have seen a surge in interest in non-singleton fuzzy systems. These systems enable the direct modelling of uncertainty affecting systems' inputs using the fuzzification stage. Moreover, recent work has shown how different composition app... Read More about An Extension of the FuzzyR Toolbox for Non-Singleton Fuzzy Logic Systems.

Designing the Hierarchical Fuzzy Systems Via FuzzyR Toolbox (2021)
Conference Proceeding
Razak, T. R., Chen, C., Garibaldi, J. M., & Wagner, C. (2021). Designing the Hierarchical Fuzzy Systems Via FuzzyR Toolbox. In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/FUZZ45933.2021.9494485

The use of Hierarchical Fuzzy Systems (HFS) has been well acknowledged as a good approach in reducing the complexity and improving the interpretability of fuzzy logic systems (FLS). Over the past years, many fuzzy logic toolkits have been made availa... Read More about Designing the Hierarchical Fuzzy Systems Via FuzzyR Toolbox.

A Fast Inference and Type-Reduction Process for Constrained Interval Type-2 Fuzzy Systems (2020)
Journal Article
D'Alterio, P., Garibaldi, J. M., John, R. I., & Wagner, C. (2021). A Fast Inference and Type-Reduction Process for Constrained Interval Type-2 Fuzzy Systems. IEEE Transactions on Fuzzy Systems, 29(11), 3323-3333. https://doi.org/10.1109/TFUZZ.2020.3018379

Constrained interval type-2 (CIT2) fuzzy sets have been introduced to preserve interpretability when moving from type-1 to interval type-2 (IT2) membership functions. Although they can be used to produce type-2 fuzzy systems with enhanced explainabil... Read More about A Fast Inference and Type-Reduction Process for Constrained Interval Type-2 Fuzzy Systems.

End-to-End Fovea Localisation in Colour Fundus Images with a Hierarchical Deep Regression Network (2020)
Journal Article
Xie, R., Liu, J., Cao, R., Qiu, C. S., Duan, J., Garibaldi, J., & Qiu, G. (2020). End-to-End Fovea Localisation in Colour Fundus Images with a Hierarchical Deep Regression Network. IEEE Transactions on Medical Imaging, 40(1), 116-128. https://doi.org/10.1109/TMI.2020.3023254

Accurately locating the fovea is a prerequisite for developing computer aided diagnosis (CAD) of retinal diseases. In colour fundus images of the retina, the fovea is a fuzzy region lacking prominent visual features and this makes it difficult to dir... Read More about End-to-End Fovea Localisation in Colour Fundus Images with a Hierarchical Deep Regression Network.

FuzzyR: An Extended Fuzzy Logic Toolbox for the R Programming Language (2020)
Conference Proceeding
Chen, C., Razak, T. R., & Garibaldi, J. M. (2020). FuzzyR: An Extended Fuzzy Logic Toolbox for the R Programming Language. In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-8). https://doi.org/10.1109/fuzz48607.2020.9177780

This paper presents an R package FuzzyR which is an extended fuzzy logic toolbox for the R programming language. FuzzyR is a continuation of the previous Fuzzy R toolboxes such as FuzzyToolkitUoN. Whilst keeping existing functionalities of the previo... Read More about FuzzyR: An Extended Fuzzy Logic Toolbox for the R Programming Language.

Towards a Framework for Capturing Interpretability of Hierarchical Fuzzy Systems - A Participatory Design Approach (2020)
Journal Article
Soria, D., Razak, T. R., Garibaldi, J. M., Pourabdollah, A., & Wagner, C. (2021). Towards a Framework for Capturing Interpretability of Hierarchical Fuzzy Systems - A Participatory Design Approach. IEEE Transactions on Fuzzy Systems, 29(5), 1160-1172. https://doi.org/10.1109/tfuzz.2020.2969901

Hierarchical fuzzy systems (HFSs) have been shown to have the potential to improve the interpretability of fuzzy logic systems (FLSs). However, challenges remain, such as: "How can we measure their interpretability?", "How can we make an informed ass... Read More about Towards a Framework for Capturing Interpretability of Hierarchical Fuzzy Systems - A Participatory Design Approach.

Deep Fuzzy Tree for Large-Scale Hierarchical Visual Classification (2019)
Journal Article
Wang, Y., Hu, Q., Zhu, P., Li, L., Lu, B., Garibaldi, J. M., & Li, X. (2020). Deep Fuzzy Tree for Large-Scale Hierarchical Visual Classification. IEEE Transactions on Fuzzy Systems, 28(7), 1395-1406. https://doi.org/10.1109/tfuzz.2019.2936801

Deep learning models often use a flat softmax layer to classify samples after feature extraction in visual classification tasks. However, it is hard to make a single decision of finding the true label from massive classes. In this scenario, hierarchi... Read More about Deep Fuzzy Tree for Large-Scale Hierarchical Visual Classification.

ADONiS - Adaptive Online Non-Singleton Fuzzy Logic Systems (2019)
Journal Article
Pekaslan, D., Wagner, C., & Garibaldi, J. M. (2020). ADONiS - Adaptive Online Non-Singleton Fuzzy Logic Systems. IEEE Transactions on Fuzzy Systems, 28(10), 2302-2312. https://doi.org/10.1109/tfuzz.2019.2933787

Non-Singleton Fuzzy Logic Systems (NSFLSs) have the potential to capture and handle input noise within the design of input fuzzy sets. In this paper, we propose an online learning method which utilises a sequence of observations to continuously updat... Read More about ADONiS - Adaptive Online Non-Singleton Fuzzy Logic Systems.

A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening (2019)
Conference Proceeding
Figueredo, G. P., Shi, P., Parkes, A. J., Evans, K., Garibaldi, J. M., Negm, O., …Robertson, J. (2019). A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening. In 2019 IEEE Congress on Evolutionary Computation (CEC) (95-102). https://doi.org/10.1109/CEC.2019.8790316

Current methods to identify cutoff values for tumour-associated molecules (antigens) discrimination are based on statistics and brute force. These methods applied to cancer screening problems are very inefficient, especially with large data sets with... Read More about A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening.

A Novel Weighted Combination Method for Feature Selection using Fuzzy Sets (2019)
Conference Proceeding
Shen, Z., Chen, X., & Garibaldi, J. M. (2019). A Novel Weighted Combination Method for Feature Selection using Fuzzy Sets. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2019.8858890

In this paper, we propose a novel weighted combination feature selection method using bootstrap and fuzzy sets. The proposed method mainly consists of three processes, including fuzzy sets generation using bootstrap, weighted combination of fuzzy set... Read More about A Novel Weighted Combination Method for Feature Selection using Fuzzy Sets.

Leveraging IT2 Input Fuzzy Sets in Non-Singleton Fuzzy Logic Systems to Dynamically Adapt to Varying Uncertainty Levels (2019)
Conference Proceeding
Pekaslan, D., Wagner, C., & Garibaldi, J. M. (2019). Leveraging IT2 Input Fuzzy Sets in Non-Singleton Fuzzy Logic Systems to Dynamically Adapt to Varying Uncertainty Levels. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-7). https://doi.org/10.1109/FUZZ-IEEE.2019.8858800

Most real-world environments are subject to different sources of uncertainty which may vary in magnitude over time. We propose that while Type-1 (T1) Non-Singleton Fuzzy Logic System (NSFLSs) have the potential to tackle uncertainty within the input... Read More about Leveraging IT2 Input Fuzzy Sets in Non-Singleton Fuzzy Logic Systems to Dynamically Adapt to Varying Uncertainty Levels.

On the Concept of Meaningfulness in Constrained Type-2 Fuzzy Sets (2019)
Conference Proceeding
D'Alterio, P., Garibaldi, J. M., & John, R. (2019). On the Concept of Meaningfulness in Constrained Type-2 Fuzzy Sets. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)https://doi.org/10.1109/FUZZ-IEEE.2019.8858942

Constrained type-2 fuzzy sets have been proposed as a tool to model type-2 fuzzy sets starting from a type-1 generator set with uncertainty. This constrained representation only defines as acceptable the embedded sets that have the same shape as the... Read More about On the Concept of Meaningfulness in Constrained Type-2 Fuzzy Sets.

Similarity between interval-valued fuzzy sets taking into account the width of the intervals and admissible orders (2019)
Journal Article
Bustince, H., Marco-Detchart, C., Fernandez, J., Wagner, C., Garibaldi, J., & Takáč, Z. (2019). Similarity between interval-valued fuzzy sets taking into account the width of the intervals and admissible orders. Fuzzy Sets and Systems, https://doi.org/10.1016/j.fss.2019.04.002

In this work we study a new class of similarity measures between interval-valued fuzzy sets. The novelty of our approach lays, firstly, on the fact that we develop all the notions with respect to total orders of intervals; and secondly, on that we co... Read More about Similarity between interval-valued fuzzy sets taking into account the width of the intervals and admissible orders.

Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems - A User Study (2018)
Conference Proceeding
Rosli Razak, T. R., Garibaldi, J. M., Wagner, C., Pourabdollah, A., & Soria, D. (2018). Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems - A User Study. In Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence (IEEE-SSCI 2018) (420-426). https://doi.org/10.1109/SSCI.2018.8628924

In recent years, researchers have become increasingly more interested in designing an interpretable Fuzzy Logic System (FLS). Many studies have claimed that reducing the complexity of FLSs can lead to improved model interpretability. That is, reducin... Read More about Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems - A User Study.

Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom (2018)
Journal Article
Figueredo, G. P., Agrawal, U., Mase, J., Mesgarpour, M., Wagner, C., Soria, D., …John, R. (2019). Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom. IEEE Transactions on Intelligent Transportation Systems, 20(9), 3324-3336. https://doi.org/10.1109/TITS.2018.2875343

Although driving behaviour has been largely studied amongst private motor vehicles drivers, the literature addressing heavy goods vehicle (HGV) drivers is scarce. Identifying the existing groups of driving stereotypes and their proportions enables re... Read More about Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom.

Noise Parameter Estimation for Non-Singleton Fuzzy Logic Systems (2018)
Conference Proceeding
Pekaslan, D., Garibaldi, J. M., & Wagner, C. (2018). Noise Parameter Estimation for Non-Singleton Fuzzy Logic Systems. In Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) ( 2960-2965). https://doi.org/10.1109/SMC.2018.00503

Real-world environments face a wide range of noise (uncertainty) sources and gaining insight into the level of noise is a critical part of many applications. While Non-Singleton Fuzzy Logic Systems (NSFLSs), in particular recently introduced advanced... Read More about Noise Parameter Estimation for Non-Singleton Fuzzy Logic Systems.

A comment on "A direct approach for determining the switch points in the Karnik-Mendel algorithm" (2018)
Journal Article
Chen, C., Wu, D., Garibaldi, J. M., John, R., Twycross, J., & Mendel, J. M. (2018). A comment on "A direct approach for determining the switch points in the Karnik-Mendel algorithm". IEEE Transactions on Fuzzy Systems, 26(6), 3905-3907. https://doi.org/10.1109/tfuzz.2018.2865134

This letter is a supplement to the previous paper “A Direct Approach for Determining the Switch Points in the Karnik-Mendel Algorithm”. In the previous paper, the enhanced iterative algorithm with stop condition (EIASC) was shown to be the most ineff... Read More about A comment on "A direct approach for determining the switch points in the Karnik-Mendel algorithm".