All Outputs (7)

On Cooperative Coevolution and Global Crossover (2024)
Journal Article
Bull, L., & Liu, H. (2024). On Cooperative Coevolution and Global Crossover. IEEE Transactions on Evolutionary Computation, 28(2), 558-561. https://doi.org/10.1109/tevc.2024.3355776

Cooperative coevolutionary algorithms (CCEAs) divide a given problem in to a number of subproblems and use an evolutionary algorithm to solve each subproblem. This letter is concerned with the scenario under which a single fitness measure exists. By... Read More about On Cooperative Coevolution and Global Crossover.

A systematic review of machine-learning solutions in anaerobic digestion (2023)
Journal Article
Rutland, H., You, J., Liu, H., Bull, L., & Reynolds, D. (2023). A systematic review of machine-learning solutions in anaerobic digestion. Bioengineering, 10(12), Article 1410. https://doi.org/10.3390/bioengineering10121410

The use of machine learning (ML) in anaerobic digestion (AD) is growing in popularity and improves the interpretation of complex system parameters for better operation and optimisation. This systematic literature review aims to explore how ML is curr... Read More about A systematic review of machine-learning solutions in anaerobic digestion.

Reproducing "Show, attend and tell: Neural image caption generation with visual attention" (2023)
Journal Article
Liu, H., & Brailsford, T. (2023). Reproducing "Show, attend and tell: Neural image caption generation with visual attention". Journal of Physics: Conference Series, 2589(1), Article 012012. https://doi.org/10.1088/1742-6596/2589/1/012012

This paper replicates the experiment presented in the work of Xu et al. [1], and examines errors in the generated captions. The analysis of the identified errors aims to provide deeper insight into the underlying causes. This study also encompass... Read More about Reproducing "Show, attend and tell: Neural image caption generation with visual attention".

A generalised dropout mechanism for distributed systems (2022)
Journal Article
Bull, L., & Liu, H. (2023). A generalised dropout mechanism for distributed systems. Artificial Life, 29(2), 146-152. https://doi.org/10.1162/artl_a_00393

This letter uses a modified form of the NK model introduced to explore aspects of distributed control. In particular, a previous result suggesting the use of dynamically formed subgroups within the overall system can be more effective than global con... Read More about A generalised dropout mechanism for distributed systems.

Optimize transfer learning for lung diseases in bronchoscopy using a new concept: Sequential fine-tuning (2018)
Journal Article
Tan, T., Li, Z., Liu, H., Zanjani, F. G., Ouyang, Q., Tang, Y., …Li, Q. (2018). Optimize transfer learning for lung diseases in bronchoscopy using a new concept: Sequential fine-tuning. IEEE Journal of Translational Engineering in Health and Medicine, 6, 1-8. https://doi.org/10.1109/JTEHM.2018.2865787

Bronchoscopy inspection, as a follow-up procedure next to the radiological imaging, plays a key role in the diagnosis and treatment design for lung disease patients. When performing bronchoscopy, doctors have to make a decision immediately whether to... Read More about Optimize transfer learning for lung diseases in bronchoscopy using a new concept: Sequential fine-tuning.

Towards computation of novel ideas from corpora of scientific text (2015)
Journal Article
Liu, H., Goulding, J., & Brailsford, T. (2015). Towards computation of novel ideas from corpora of scientific text. Lecture Notes in Artificial Intelligence, 9285, 541-556. https://doi.org/10.1007/978-3-319-23525-7_33

© Springer International Publishing Switzerland 2015. In this work we present a method for the computation of novel ‘ideas’ from corpora of scientific text. The system functions by first detecting concept noun-phrases within the titles and abstracts... Read More about Towards computation of novel ideas from corpora of scientific text.

Incorporating texture features in a computer-aided breast lesion diagnosis system for automated three-dimensional breast ultrasound (2014)
Journal Article
Liu, H., Tan, T., Van Zelst, J., Mann, R., Karssemeijer, N., & Platel, B. (2014). Incorporating texture features in a computer-aided breast lesion diagnosis system for automated three-dimensional breast ultrasound. Journal of Medical Imaging, 1(2), 024501. https://doi.org/10.1117/1.JMI.1.2.024501

We investigated the benefits of incorporating texture features into an existing computer-aided diagnosis (CAD) system for classifying benign and malignant lesions in automated three-dimensional breast ultrasound images. The existing system takes into... Read More about Incorporating texture features in a computer-aided breast lesion diagnosis system for automated three-dimensional breast ultrasound.