Outputs (73)

Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis (2017)
Journal Article
Poria, S., Peng, H., Hussain, A., Howard, N., & Cambria, E. (2017). Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis. Neurocomputing, 261, 217-230. https://doi.org/10.1016/j.neucom.2016.0

The advent of the Social Web has enabled anyone with an Internet connection to easily create and share their ideas, opinions and content with millions of other people around the world. In pace with a global deluge of videos from billions of computers... Read More about Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis.

A review of affective computing: From unimodal analysis to multimodal fusion (2017)
Journal Article
Poria, S., Cambria, E., Bajpai, R., & Hussain, A. (2017). A review of affective computing: From unimodal analysis to multimodal fusion. Information Fusion, 37, 98-125. https://doi.org/10.1016/j.inffus.2017.02.003

Affective computing is an emerging interdisciplinary research field bringing together researchers and practitioners from various fields, ranging from artificial intelligence, natural language processing, to cognitive and social sciences. With the pro... Read More about A review of affective computing: From unimodal analysis to multimodal fusion.

Ensemble based majority voting for point-to-point measurements of Gyrodactylus species identification (2017)
Journal Article
Ali, R., Hussain, A., & Abel, A. (2017). Ensemble based majority voting for point-to-point measurements of Gyrodactylus species identification. ARPN Journal of Engineering and Applied Sciences, 12(2), 310-316

In the 21st Century, a key challenge in both wild and cultured fish populations for control and management of disease is to securely and consistently perform pathogen identification. To provide automated accurate classification for the challeng... Read More about Ensemble based majority voting for point-to-point measurements of Gyrodactylus species identification.

BEFTIGRE: Behaviour-driven full-tier green evaluation of mobile cloud applications (2017)
Journal Article
Chinenyeze, S. J., Liu, X., & Al-Dubai, A. (2017). BEFTIGRE: Behaviour-driven full-tier green evaluation of mobile cloud applications. Journal of Software: Evolution and Process, 29(2), e1848. https://doi.org/10.1002/smr.1848

With the resource-constrained nature of mobile devices and the resource-abundant offerings of the cloud, several promising optimisation techniques have been proposed by the green computing research community. Prominent techniques and unique methods h... Read More about BEFTIGRE: Behaviour-driven full-tier green evaluation of mobile cloud applications.

High-dimensional function approximation with neural networks for large volumes of data (2017)
Journal Article
Andras, P. (2018). High-dimensional function approximation with neural networks for large volumes of data. IEEE Transactions on Neural Networks and Learning Systems, 29(2), 500-508. https://doi.org/10.1109/TNNLS.2017.2651985

Approximation of high-dimensional functions is a challenge for neural networks due to the curse of dimensionality. Often the data for which the approximated function is defined resides on a low-dimensional manifold and in principle the approximation... Read More about High-dimensional function approximation with neural networks for large volumes of data.

A neuro-inspired visual tracking method based on programmable system-on-chip platform (2017)
Journal Article
Yang, S., Wong-Lin, K., Andrew, J., Mak, T., & McGinnity, T. M. (2018). A neuro-inspired visual tracking method based on programmable system-on-chip platform. Neural Computing and Applications, 30(9), 2697-2708. https://doi.org/10.1007/s00521-017-2847-5

Using programmable system-on-chip to implement computer vision functions poses many challenges due to highly constrained resources in cost, size and power consumption. In this work, we propose a new neuro-inspired image processing model and implement... Read More about A neuro-inspired visual tracking method based on programmable system-on-chip platform.

10Gbit/s mode-multiplexed QPSK transmission using MDM-to-MFDM based single coherent receiver for intra- and inter data center networking (2017)
Journal Article
Asif, R., & Haithem, M. (2017). 10Gbit/s mode-multiplexed QPSK transmission using MDM-to-MFDM based single coherent receiver for intra- and inter data center networking. Optics Communications, 391, 106-110. https://doi.org/10.1016/j.optcom.2017.01.022

Generalized few-mode-fiber (FMF) transmission uses N coherent receivers for mode detection, where N scales with the number of fiber modes. Multiple coherent receivers increase the cost of optical network units (ONUs) in access networks, specifically... Read More about 10Gbit/s mode-multiplexed QPSK transmission using MDM-to-MFDM based single coherent receiver for intra- and inter data center networking.

On the comparison of initialisation strategies in differential evolution for large scale optimisation (2017)
Journal Article
Segredo, E., Paechter, B., Segura, C., & González-Vila, C. I. (2018). On the comparison of initialisation strategies in differential evolution for large scale optimisation. Optimization Letters, 12(1), 221-234. https://doi.org/10.1007/s11590-017-1107-z

Differential Evolution (DE) has shown to be a promising global opimisation solver for continuous problems, even for those with a large dimensionality. Different previous works have studied the effects that a population initialisation strategy has on... Read More about On the comparison of initialisation strategies in differential evolution for large scale optimisation.

On Constructing Ensembles for Combinatorial Optimisation (2017)
Journal Article
Hart, E., & Sim, K. (2018). On Constructing Ensembles for Combinatorial Optimisation. Evolutionary Computation, 26(1), 67-87. https://doi.org/10.1162/evco_a_00203

Although the use of ensemble methods in machine-learning is ubiquitous due to their proven ability to outperform their constituent algorithms, ensembles of optimisation algorithms have received relatively little attention. Existing approaches lag beh... Read More about On Constructing Ensembles for Combinatorial Optimisation.

Educational affordances and learning design in music software development (2017)
Journal Article
Cheng, L., & Leong, S. (2017). Educational affordances and learning design in music software development. Technology, Pedagogy and Education, 26(4), 395-407. https://doi.org/10.1080/1475939x.2016.1267037

Although music software has become increasingly affordable and widely adopted in today’s classrooms, concerns have been raised about a lack of consideration for users’ needs during the software development process. This paper examines intra- and inte... Read More about Educational affordances and learning design in music software development.