Outputs (4095)

Deep and sparse learning in speech and language processing: An overview (2016)
Presentation / Conference Contribution
Wang, D., Zhou, Q., & Hussain, A. (2016, November). Deep and sparse learning in speech and language processing: An overview. Presented at BICS 2016: International Conference on Brain Inspired Cognitive Systems, Beijing, China

Large-scale deep neural models, e.g., deep neural networks (DNN) and recurrent neural networks (RNN), have demonstrated significant success in solving various challenging tasks of speech and language processing (SLP), including speech recognition, sp... Read More about Deep and sparse learning in speech and language processing: An overview.

Modified cat swarm optimization for clustering (2016)
Presentation / Conference Contribution
Razzaq, S., Maqbool, F., & Hussain, A. (2016, November). Modified cat swarm optimization for clustering. Presented at BICS 2016: International Conference on Brain Inspired Cognitive Systems, Beijing, China

Clustering is one of the most challenging optimization problems. Many Swarm Intelligence techniques including Ant Colony optimization (ACO), Particle Swarm Optimization (PSO), and Honey Bee Optimization (HBO) have been used to solve clustering. Cat S... Read More about Modified cat swarm optimization for clustering.

A novel fully automated liver and HCC tumor segmentation system using morphological operations (2016)
Presentation / Conference Contribution
Ali, L., Hussain, A., Li, J., Howard, N., Shah, A., Sudhakar, U., Shah, M., & Hussain, Z. (2016, November). A novel fully automated liver and HCC tumor segmentation system using morphological operations. Presented at 8th International Conference, BICS 2016, Beijing, China

Early detection and diagnosis of Hepatocellular Carcinoma (HCC) is the most discriminating step in liver cancer management. Image processing is primarily used, where fast and accurate Computed Tomography (CT) liver image segmentation is required for... Read More about A novel fully automated liver and HCC tumor segmentation system using morphological operations.

A new biologically-inspired analytical worm propagation model for mobile unstructured peer-to-peer networks (2016)
Presentation / Conference Contribution
Alharbi, H., Aloufi, K., & Hussain, A. (2016, November). A new biologically-inspired analytical worm propagation model for mobile unstructured peer-to-peer networks. Presented at 8th International Conference, BICS 2016, Beijing, China

Millions of users world-wide are sharing content using the Peer-to-Peer (P2P) client network. While new innovations bring benefits, there are nevertheless some dangers associated with them. One of the main threats is P2P worms that can penetrate the... Read More about A new biologically-inspired analytical worm propagation model for mobile unstructured peer-to-peer networks.

PerSent: A freely available Persian sentiment lexicon (2016)
Presentation / Conference Contribution
Dashtipour, K., Hussain, A., Zhou, Q., Gelbukh, A., Hawalah, A. Y. A., & Cambria, E. (2016, November). PerSent: A freely available Persian sentiment lexicon. Presented at BICS 2016: International Conference on Brain Inspired Cognitive Systems, Beijing, China

People need to know other people’s opinions to make well-informed decisions to buy products or services. Companies and organizations need to understand people’s attitude towards their products and services and use feedback from the customers to impro... Read More about PerSent: A freely available Persian sentiment lexicon.

Predicting insulin resistance in children using a machine-learning-based clinical decision support system (2016)
Presentation / Conference Contribution
Hall, A. J., Hussain, A., & Shaikh, M. G. (2016, November). Predicting insulin resistance in children using a machine-learning-based clinical decision support system. Presented at BICS 2016: International Conference on Brain Inspired Cognitive Systems, Beijing, China

This study proposes a new diagnostic approach based on application of machine learning techniques to anthropometric patient features in order to create a predictive model capable of diagnosing insulin resistance (HOMA-IR).

As part of the study, a... Read More about Predicting insulin resistance in children using a machine-learning-based clinical decision support system.

Visual attention model with a novel learning strategy and its application to target detection from SAR images (2016)
Presentation / Conference Contribution
Gao, F., Xue, X., Wang, J., Sun, J., Hussain, A., & Yang, E. (2016, November). Visual attention model with a novel learning strategy and its application to target detection from SAR images. Presented at BICS 2016: International Conference on Brain Inspired Cognitive Systems, Beijing, China

The selective visual attention mechanism in human visual system helps human to act efficiently when dealing with massive visual information. Over the last two decades, biologically inspired attention model has drawn lots of research attention and man... Read More about Visual attention model with a novel learning strategy and its application to target detection from SAR images.

A data driven approach to audiovisual speech mapping (2016)
Presentation / Conference Contribution
Abel, A., Marxer, R., Barker, J., Watt, R., Whitmer, B., Derleth, P., & Hussain, A. (2016, November). A data driven approach to audiovisual speech mapping. Presented at 8th International Conference, BICS 2016, Beijing, China

The concept of using visual information as part of audio speech processing has been of significant recent interest. This paper presents a data driven approach that considers estimating audio speech acoustics using only temporal visual information wit... Read More about A data driven approach to audiovisual speech mapping.

How to Talk to Strangers: generating medical reports for first time users (2016)
Presentation / Conference Contribution
Gkatzia, D., Rieser, V., & Lemon, O. (2016, July). How to Talk to Strangers: generating medical reports for first time users. Presented at FUZZ-IEEE 2016

We propose a novel approach for handling first-time
users in the context of automatic report generation from timeseries
data in the health domain. Handling first-time users is
a common problem for Natural Language Generation (NLG)
and interactive... Read More about How to Talk to Strangers: generating medical reports for first time users.

Tagore's School and Methodology: Classrooms Without Walls (2016)
Journal Article
Kane, T. (2016). Tagore's School and Methodology: Classrooms Without Walls. Gitanjali and Beyond, 1(1), 83. https://doi.org/10.14297/gnb.1.1.83-101

This paper argues that Rabindranath Tagore, a very practical man, developed a distinctive and successful educational methodology over the course of his work in educational systems. The paper seeks to show that Tagore drew inspiration and direction fr... Read More about Tagore's School and Methodology: Classrooms Without Walls.