Outputs (28)

Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings (2020)
Presentation / Conference Contribution
(2019, July). Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings. Presented at BICS: International Conference on Brain Inspired Cognitive Systems, Guangzhou, China

This book constitutes the refereed proceedings of the 10th International Conference on Advances in Brain Inspired Cognitive Systems, BICS 2019, held in Guangzhou, China, in July 2019. The 57 papers presented in this volume were carefully reviewed... Read More about Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings.

Design and evaluation of a biologically-inspired cloud elasticity framework (2020)
Journal Article
Ullah, A., Li, J., & Hussain, A. (2020). Design and evaluation of a biologically-inspired cloud elasticity framework. Cluster Computing, 23, 3095-3117. https://doi.org/10.1007/s10586-020-03073-7

The elasticity in cloud is essential to the effective management of computational resources as it enables readjustment at runtime to meet application demands. Over the years, researchers and practitioners have proposed many auto-scaling solutions usi... Read More about Design and evaluation of a biologically-inspired cloud elasticity framework.

Impact of Relay Location of STANC Bi-Directional Transmission for Future Autonomous Internet of Things Applications (2020)
Journal Article
Tanoli, S. A. K., Shah, S. A., Khan, M. B., Nawaz, F., Hussain, A., Al-Dubai, A. Y., Khan, I., Shah, S. Y., & Alsarhan, A. (2020). Impact of Relay Location of STANC Bi-Directional Transmission for Future Autonomous Internet of Things Applications. IEEE Access, 8, 29395-29406. https://doi.org/10.1109/access.2020.2969750

Wireless communication using existing coding models poses several challenges for RF signals due to multipath scattering, rapid fluctuations in signal strength and path loss effect. Unlike existing works, this study presents a novel cod... Read More about Impact of Relay Location of STANC Bi-Directional Transmission for Future Autonomous Internet of Things Applications.

Self-focus Deep Embedding Model for Coarse-Grained Zero-Shot Classification (2020)
Presentation / Conference Contribution
Yang, G., Huang, K., Zhang, R., Goulermas, J. Y., & Hussain, A. (2019, July). Self-focus Deep Embedding Model for Coarse-Grained Zero-Shot Classification. Presented at 10th International Conference, BICS 2019, Guangzhou, China

Zero-shot learning (ZSL), i.e. classifying patterns where there is a lack of labeled training data, is a challenging yet important research topic. One of the most common ideas for ZSL is to map the data (e.g., images) and semantic attributes to the s... Read More about Self-focus Deep Embedding Model for Coarse-Grained Zero-Shot Classification.

Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances (2020)
Presentation / Conference Contribution
Ahmed, R., Dashtipour, K., Gogate, M., Raza, A., Zhang, R., Huang, K., Hawalah, A., Adeel, A., & Hussain, A. (2019, July). Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances. Presented at 10th International Conference, BICS 2019, Guangzhou, China

In pattern recognition, automatic handwriting recognition (AHWR) is an area of research that has developed rapidly in the last few years. It can play a significant role in broad-spectrum of applications rending from, bank cheque processing, applicati... Read More about Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances.

Height Prediction for Growth Hormone Deficiency Treatment Planning Using Deep Learning (2020)
Presentation / Conference Contribution
Ilyas, M., Ahmad, J., Lawson, A., Khan, J. S., Tahir, A., Adeel, A., Larijani, H., Kerrouche, A., Shaikh, M. G., Buchanan, W., & Hussain, A. (2019, July). Height Prediction for Growth Hormone Deficiency Treatment Planning Using Deep Learning. Presented at 10th International Conference, BICS 2019, Guangzhou, China

Prospective studies using longitudinal patient data can be used to help to predict responsiveness to Growth Hormone (GH) therapy and assess any suspected risks. In this paper, a novel Clinical Decision Support System (CDSS) is developed to predict gr... Read More about Height Prediction for Growth Hormone Deficiency Treatment Planning Using Deep Learning.

Generalized Adversarial Training in Riemannian Space (2020)
Presentation / Conference Contribution
Zhang, S., Huang, K., Zhang, R., & Hussain, A. (2020). Generalized Adversarial Training in Riemannian Space. In 2019 IEEE International Conference on Data Mining (ICDM) (826-835). https://doi.org/10.1109/icdm.2019.00093

Adversarial examples, referred to as augmented data points generated by imperceptible perturbations of input samples, have recently drawn much attention. Well-crafted adversarial examples may even mislead state-of-the-art deep neural network (DNN) mo... Read More about Generalized Adversarial Training in Riemannian Space.

Random Features and Random Neurons for Brain-Inspired Big Data Analytics (2020)
Presentation / Conference Contribution
Gogate, M., Hussain, A., & Huang, K. (2019, November). Random Features and Random Neurons for Brain-Inspired Big Data Analytics. Presented at 2019 International Conference on Data Mining Workshops (ICDMW), Beijing, China

With the explosion of Big Data, fast and frugal reasoning algorithms are increasingly needed to keep up with the size and the pace of user-generated contents on the Web. In many real-time applications, it is preferable to be able to process more data... Read More about Random Features and Random Neurons for Brain-Inspired Big Data Analytics.