All Outputs (11)

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.

A classification-regression deep learning model for people counting (2018)
Conference Proceeding
Xu, B., Zou, W., Garibaldi, J., & Qiu, G. (2018). A classification-regression deep learning model for people counting. In K. Arai, S. Kapoor, & R. Bhatia (Eds.), Intelligent Systems and Applications Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 1 (136-149). https://doi.org/10.1007/978-3-030-01054-6_9

In this paper, we construct a multi-task deep learning model to simultaneously predict people number and the level of crowd density. Motivated by the success of applying " ambiguous labelling " to age estimation problem, we also manage to employ this... Read More about A classification-regression deep learning model for people counting.

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.

An end-to-end deep learning histochemical scoring system for breast cancer TMA (2018)
Journal Article
Liu, J., Xu, B., Zheng, C., Gong, Y., Garibaldi, J., Soria, D., …Qiu, G. (2019). An end-to-end deep learning histochemical scoring system for breast cancer TMA. IEEE Transactions on Medical Imaging, 38(2), 617-628. https://doi.org/10.1109/TMI.2018.2868333

One of the methods for stratifying different molecular classes of breast cancer is the Nottingham prognostic index plus, which uses breast cancer relevant biomarkers to stain tumor tissues prepared on tissue microarray (TMA). To determine the molecul... Read More about An end-to-end deep learning histochemical scoring system for breast cancer TMA.

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".

Exploring subsethood to determine firing strength in non-singleton fuzzy logic systems (2018)
Conference Proceeding
Pekaslan, D., Garibaldi, J. M., & Wagner, C. (2018). Exploring subsethood to determine firing strength in non-singleton fuzzy logic systems.

Real world environments face a wide range of sources of noise and uncertainty. Thus, the ability to handle various uncertainties, including noise, becomes an indispensable element of automated decision making. Non-Singleton Fuzzy Logic Systems (NSFLS... Read More about Exploring subsethood to determine firing strength in non-singleton fuzzy logic systems.

Exploring Constrained Type-2 fuzzy sets (2018)
Conference Proceeding
D’Alterio, P., Garibaldi, J. M., & Pourabdollah, A. (2018). Exploring Constrained Type-2 fuzzy sets.

Fuzzy logic has been widely used to model human reasoning thanks to its inherent capability of handling uncertainty. In particular, the introduction of Type-2 fuzzy sets added the possibility of expressing uncertainty even on the definition of the me... Read More about Exploring Constrained Type-2 fuzzy sets.

Direct Application of Convolutional Neural Network Features to Image Quality Assessment (2018)
Conference Proceeding
Hou, X., Sun, K., Liu, B., Gong, Y., Garibaldi, J., & Qiu, G. (2018). Direct Application of Convolutional Neural Network Features to Image Quality Assessment. In 2018 IEEE Visual Communications and Image Processing (VCIP). https://doi.org/10.1109/VCIP.2018.8698726

© 2018 IEEE. We take advantage of the popularity of deep con-volutional neural networks (CNNs) and have developed a very simple image quality assessment method that rivals state of the art. We show that convolutional layer outputs (deep features) of... Read More about Direct Application of Convolutional Neural Network Features to Image Quality Assessment.

Comparison of fuzzy integral-fuzzy measure based ensemble algorithms with the state-of-the-art ensemble algorithms (2018)
Conference Proceeding
Agrawal, U., Pinar, A. J., Wagner, C., Havens, T. C., Soria, D., & Garibaldi, J. M. (2018). Comparison of fuzzy integral-fuzzy measure based ensemble algorithms with the state-of-the-art ensemble algorithms.

The Fuzzy Integral (FI) is a non-linear aggregation operator which enables the fusion of information from multiple sources in respect to a Fuzzy Measure (FM) which captures the worth of both the individual sources and all their possible combinations.... Read More about Comparison of fuzzy integral-fuzzy measure based ensemble algorithms with the state-of-the-art ensemble algorithms.

Input uncertainty sensitivity enhanced non-singleton fuzzy logic controllers for long-term navigation of quadrotor UAVs (2018)
Journal Article
Fu, C., Sarabakha, A., Kayacan, E., Wagner, C., John, R., & Garibaldi, J. M. (2018). Input uncertainty sensitivity enhanced non-singleton fuzzy logic controllers for long-term navigation of quadrotor UAVs. IEEE/ASME Transactions on Mechatronics, 23(2), 725-734. https://doi.org/10.1109/TMECH.2018.2810947

Input uncertainty, e.g., noise on the on-board camera and inertial measurement unit, in vision-based control of unmanned aerial vehicles (UAVs) is an inevitable problem. In order to handle input uncertainties as well as further analyze the interactio... Read More about Input uncertainty sensitivity enhanced non-singleton fuzzy logic controllers for long-term navigation of quadrotor UAVs.