Outputs (400)

Extracting Time Expressions and Named Entities with Constituent-Based Tagging Schemes (2020)
Journal Article
Zhong, X., Cambria, E., & Hussain, A. (2020). Extracting Time Expressions and Named Entities with Constituent-Based Tagging Schemes. Cognitive Computation, 12, 844-862. https://doi.org/10.1007/s12559-020-09714-8

Time expressions and named entities play important roles in data mining, information retrieval, and natural language processing. However, the conventional position-based tagging schemes (e.g., the BIO and BILOU schemes) that previous research used to... Read More about Extracting Time Expressions and Named Entities with Constituent-Based Tagging Schemes.

CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement (2020)
Journal Article
Gogate, M., Dashtipour, K., Adeel, A., & Hussain, A. (2020). CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement. Information Fusion, 63, 273-285. https://doi.org/10.1016/j.inffus.2020.04.001

Noisy situations cause huge problems for the hearing-impaired, as hearing aids often make speech more audible but do not always restore intelligibility. In noisy settings, humans routinely exploit the audio-visual (AV) nature of speech to selectively... Read More about CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement.

Novel deep neural network based pattern field classification architectures (2020)
Journal Article
Huang, K., Zhang, S., Zhang, R., & Hussain, A. (2020). Novel deep neural network based pattern field classification architectures. Neural Networks, 127, 82-95. https://doi.org/10.1016/j.neunet.2020.03.011

Field classification is a new extension of traditional classification frameworks that attempts to utilize consistent information from a group of samples (termed fields). By forgoing the independent identically distributed (i.i.d.) assumption, field c... Read More about Novel deep neural network based pattern field classification architectures.

BrainOS: A Novel Artificial Brain-Alike Automatic Machine Learning Framework (2020)
Journal Article
Howard, N., Chouikhi, N., Adeel, A., Dial, K., Howard, A., & Hussain, A. (2020). BrainOS: A Novel Artificial Brain-Alike Automatic Machine Learning Framework. Frontiers in Computational Neuroscience, 14, https://doi.org/10.3389/fncom.2020.00016

Human intelligence is constituted by a multitude of cognitive functions activated either directly or indirectly by external stimuli of various kinds. Computational approaches to the cognitive sciences and to neuroscience are partly premised on the id... Read More about BrainOS: A Novel Artificial Brain-Alike Automatic Machine Learning Framework.

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.

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.

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.