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All Outputs (477)

Visual Attention Model Based Vehicle Target Detection in Synthetic Aperture Radar Images: A Novel Approach (2014)
Journal Article
Gao, F., Zhang, Y., Wang, J., Sun, J., Yang, E., & Hussain, A. (2015). Visual Attention Model Based Vehicle Target Detection in Synthetic Aperture Radar Images: A Novel Approach. Cognitive Computation, 7(4), 434-444. https://doi.org/10.1007/s12559-014-931

The human visual system (HVS) possesses a remarkable ability of real-time complex scene analysis despite the limited neuronal hardware available for such tasks. The HVS successfully overcomes the problem of information bottleneck by selecting potenti... Read More about Visual Attention Model Based Vehicle Target Detection in Synthetic Aperture Radar Images: A Novel Approach.

Towards an intelligent framework for multimodal affective data analysis (2014)
Journal Article
Poria, S., Cambria, E., Hussain, A., & Huang, G. (2015). Towards an intelligent framework for multimodal affective data analysis. Neural Networks, 63, 104-116. https://doi.org/10.1016/j.neunet.2014.10.005

An increasingly large amount of multimodal content is posted on social media websites such as YouTube and Facebook everyday. In order to cope with the growth of such so much multimodal data, there is an urgent need to develop an intelligent multi-mod... Read More about Towards an intelligent framework for multimodal affective data analysis.

Dependency tree-based rules for concept-level aspect-based sentiment analysis (2014)
Presentation / Conference Contribution
Poria, S., Ofek, N., Gelbukh, A., Hussain, A., & Rokach, L. (2014). Dependency tree-based rules for concept-level aspect-based sentiment analysis. In Semantic Web Evaluation Challenge: SemWebEval 2014 at ESWC 2014, Anissaras, Crete, Greece, May 25-29, 20

Over the last few years, the way people express their opinions has changed dramatically with the progress of social networks, web communities, blogs, wikis, and other online collaborative media. Now, people buy a product and express their opinion in... Read More about Dependency tree-based rules for concept-level aspect-based sentiment analysis.

AspNet: Aspect Extraction by Bootstrapping Generalization and Propagation Using an Aspect Network (2014)
Journal Article
Xia, Y., Cambria, E., & Hussain, A. (2015). AspNet: Aspect Extraction by Bootstrapping Generalization and Propagation Using an Aspect Network. Cognitive Computation, 7(2), 241-253. https://doi.org/10.1007/s12559-014-9305-9

Aspect-level opinion mining systems suffer from concept coverage problem due to the richness and ambiguity of natural language opinions. Aspects mentioned by review authors can be expressed in various forms, resulting in a potentially large number of... Read More about AspNet: Aspect Extraction by Bootstrapping Generalization and Propagation Using an Aspect Network.

Word Polarity Disambiguation Using Bayesian Model and Opinion-Level Features (2014)
Journal Article
Xia, Y., Cambria, E., Hussain, A., & Zhao, H. (2015). Word Polarity Disambiguation Using Bayesian Model and Opinion-Level Features. Cognitive Computation, 7(3), 369-380. https://doi.org/10.1007/s12559-014-9298-4

Contextual polarity ambiguity is an important problem in sentiment analysis. Many opinion keywords carry varying polarities in different contexts, posing huge challenges for sentiment analysis research. Previous work on contextual polarity disambigua... Read More about Word Polarity Disambiguation Using Bayesian Model and Opinion-Level Features.

EmoSenticSpace: A novel framework for affective common-sense reasoning (2014)
Journal Article
Poria, S., Gelbukh, A., Cambria, E., Hussain, A., & Huang, G. (2014). EmoSenticSpace: A novel framework for affective common-sense reasoning. Knowledge-Based Systems, 69, 108-123. https://doi.org/10.1016/j.knosys.2014.06.011

Emotions play a key role in natural language understanding and sensemaking. Pure machine learning usually fails to recognize and interpret emotions in text accurately. The need for knowledge bases that give access to semantics and sentics (the concep... Read More about EmoSenticSpace: A novel framework for affective common-sense reasoning.

A Cognitively Inspired Approach to Two-Way Cluster Extraction from One-Way Clustered Data (2014)
Journal Article
Abdullah, A., & Hussain, A. (2015). A Cognitively Inspired Approach to Two-Way Cluster Extraction from One-Way Clustered Data. Cognitive Computation, 7(1), 161-182. https://doi.org/10.1007/s12559-014-9281-0

Cluster extraction is a vital part of data mining; however, humans and computers perform it very differently. Humans tend to estimate, perceive or visualize clusters cognitively, while digital computers either perform an exact extraction, follow a fu... Read More about A Cognitively Inspired Approach to Two-Way Cluster Extraction from One-Way Clustered Data.

Novel Biologically Inspired Approaches to Extracting Online Information from Temporal Data (2014)
Journal Article
Malik, Z. K., Hussain, A., & Wu, J. (2014). Novel Biologically Inspired Approaches to Extracting Online Information from Temporal Data. Cognitive Computation, 6(3), 595-607. https://doi.org/10.1007/s12559-014-9257-0

In this paper, we aim to develop novel learning approaches for extracting invariant features from time series. Specifically, we implement an existing method of solving the generalized eigenproblem and use this to firstly implement the biologically in... Read More about Novel Biologically Inspired Approaches to Extracting Online Information from Temporal Data.

A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle (2013)
Presentation / Conference Contribution
Yang, E., Hussain, A., & Gurney, K. (2013). A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle. In Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China,

This paper presents a new brain-inspired, switching control approach for a car-like autonomous vehicle using a basal ganglia (BG) model as an action selection mechanism. The problem domain has challenging nonholonomic and state constraints which impl... Read More about A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle.

A novel SAR target detection algorithm based on contextual knowledge (2013)
Journal Article
Gao, F., Ru, A., Sun, J., & Hussain, A. (2013). A novel SAR target detection algorithm based on contextual knowledge. Progress In Electromagnetics Research, 142, 123-140. https://doi.org/10.2528/PIER13062403

This paper proposes a Synthetic Aperture Radar (SAR) vehicle target detection algorithm based on contextual knowledge. The proposed algorithm firstly obtains the general classification of SAR image with a Markov Random Field (MRF)-based segmentation... Read More about A novel SAR target detection algorithm based on contextual knowledge.

A novel clinical expert system for chest pain risk assessment (2013)
Presentation / Conference Contribution
Farooq, K., Hussain, A., Atassi, H., Leslie, S., Eckl, C., MacRae, C., & Slack, W. (2013). A novel clinical expert system for chest pain risk assessment. In Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, C

Rapid access chest pain clinics (RACPC) enable clinical risk assessment, investigation and arrangement of a treatment plan for chest pain patients without a long waiting list. RACPC Clinicians often experience difficulties in the diagnosis of chest p... Read More about A novel clinical expert system for chest pain risk assessment.

A review of artificial intelligence and biologically inspired computational approaches to solving issues in narrative financial disclosure (2013)
Presentation / Conference Contribution
Minhas, S., Poria, S., Hussain, A., & Hussainey, K. (2013). A review of artificial intelligence and biologically inspired computational approaches to solving issues in narrative financial disclosure. In Advances in Brain Inspired Cognitive Systems: 6th I

Indisputably, financial reporting has a key role to play in the efficient workings of capitalist economies. Problems related to agency and asymmetric information (Jensen and Meckling, 1976) would abound and cripple financial markets, as it has done w... Read More about A review of artificial intelligence and biologically inspired computational approaches to solving issues in narrative financial disclosure.

Cognitive computation: A case study in cognitive control of autonomous systems and some future directions (2013)
Presentation / Conference Contribution
Hussain, A. (2013). Cognitive computation: A case study in cognitive control of autonomous systems and some future directions. In The 2013 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/IJCNN.2013.6706716

Cognitive computation is an emerging discipline linking together neurobiology, cognitive psychology and artificial intelligence. Springer Neuroscience has launched a journal in this exciting multidisciplinary topic, which seeks to publish biologicall... Read More about Cognitive computation: A case study in cognitive control of autonomous systems and some future directions.

Conceptual clustering of documents for automatic ontology generation (2013)
Presentation / Conference Contribution
Krishnan, R., Hussain, A., & Sherimon, S. P. C. (2013). Conceptual clustering of documents for automatic ontology generation. In Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proce

In Information retrieval, Keyword based retrieval is unsatisfactory for user needs since it can’t always retrieve relevant words according to the concept. Since different words can represent the same concept (polysemy) and one word can represent diff... Read More about Conceptual clustering of documents for automatic ontology generation.

Efficient clinical decision making by learning from missing clinical data (2013)
Presentation / Conference Contribution
Farooq, K., Yang, P., Hussain, A., Huang, K., MacRae, C., Eckl, C., & Slack, W. (2013). Efficient clinical decision making by learning from missing clinical data. In 2013 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE) (2

Clinical decision making frequently involves making decisions under uncertainty because of missing key patient data (e.g, demographics, episodic and clinical diagnosis details) - this information is essential for modern clinical decision support syst... Read More about Efficient clinical decision making by learning from missing clinical data.

Improved efficiency of road sign detection and recognition by employing Kalman filter (2013)
Presentation / Conference Contribution
Zakir, U., Hussain, A., Ali, L., & Luo, B. (2013). Improved efficiency of road sign detection and recognition by employing Kalman filter. In Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China, June 9-11,

This paper describes an efficient approach towards road sign detection, and recognition. The proposed system is divided into three sections namely: Road Sign Detection where Colour Segmentation of the road traffic signs is carried out using HSV colou... Read More about Improved efficiency of road sign detection and recognition by employing Kalman filter.

Advances in Brain Inspired Cognitive Systems: Preface (2013)
Presentation / Conference Contribution
Liu, D., Alippi, C., Zhao, D., & Hussain, A. (2013). Advances in Brain Inspired Cognitive Systems: Preface. . https://doi.org/10.1007/978-3-642-38786-9

This book constitutes the refereed proceedings of the 6th International Conference on Brain Inspired Cognitive Systems, BICS 2013, held in Beijing, China in June 2013. The 45 high-quality papers presented were carefully reviewed and selected from 68... Read More about Advances in Brain Inspired Cognitive Systems: Preface.

Music genre classification: A semi-supervised approach (2013)
Presentation / Conference Contribution
Poria, S., Gelbukh, A., Hussain, A., Bandyopadhyay, S., & Howard, N. (2013). Music genre classification: A semi-supervised approach. In Pattern Recognition: 5th Mexican Conference, MCPR 2013, Querétaro, Mexico, June 26-29, 2013. Proceedings (254-263). h

Music genres can be seen as categorical descriptions used to classify music basing on various characteristics such as instrumentation, pitch, rhythmic structure, and harmonic contents. Automatic music genre classification is important for music retri... Read More about Music genre classification: A semi-supervised approach.