All Outputs (6)

Effective pixel classification of Mars images based on ant colony optimization feature selection and extreme learning machine (2016)
Journal Article
Rashno, A., Nazari, B., Sadri, S., & Saraee, M. (2017). Effective pixel classification of Mars images based on ant colony optimization feature selection and extreme learning machine. Neurocomputing, 226, 66-79. https://doi.org/10.1016/j.neucom.2016.11.030

one of the most important tasks of Mars rover, a robot which explores the Mars surface, is the process of automatic segmentation of images taken by front-line Panoramic Camera (Pancam). This procedure is highly significant since the transformation co... Read More about Effective pixel classification of Mars images based on ant colony optimization feature selection and extreme learning machine.

Mining the crime survey to support crime profiling (2016)
Presentation / Conference
Wu, J., Meziane, F., Saraee, M., Aspin, R., & Hope, T. (2016, October). Mining the crime survey to support crime profiling. Presented at 2016 International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM), Reggio Calabria, Italy

Crime surveys are conducted to record crimes by the Office for National Statistics (ONS) in the United Kingdom every year. They contain rich information about crime. They record the crimes that are not reported to the police. However, their exploitat... Read More about Mining the crime survey to support crime profiling.

Semantic aware Bayesian network model for actionable knowledge discovery in linked data (2016)
Presentation / Conference
Alharbi, H., & Saraee, M. (2016, July). Semantic aware Bayesian network model for actionable knowledge discovery in linked data. Presented at 12th International Conference, MLDM 2016, New York, NY, USA

The majority of the conventional mining algorithms treat the mining process as an isolated data-driven procedure and overlook the semantic of the targeted data. As a result, the generated patterns are abundant and end users cannot act upon them seaml... Read More about Semantic aware Bayesian network model for actionable knowledge discovery in linked data.

A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments (2016)
Journal Article
Al-Nawashi, M., Al-Hazaimeh, O., & Saraee, M. (2016). A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments. Neural Computing and Applications, 27(4), https://doi.org/10.1007/s00521-016-2363-z

Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system thatcan perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic re... Read More about A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments.

Natural language processing and information systems : 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings (2016)
Book
(2016). E. Metais, F. Meziane, M. Saraee, V. Sugumaran, S. Vadera, E. Métais, …S. Vadera (Eds.), Natural language processing and information systems : 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings. Springer. https://doi.org/10.1007/978-3-319-41754-7

This volume of the lecture notes in computer science (LNCS) contains the papers presented at the 21st International Conference on application of Natural Language to Information Systems, held at MediacityUK, University of Salford on the 22-24 June 201... Read More about Natural language processing and information systems : 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings.

Simulated annealing least squares twin support vector machine (SA-LSTSVM) for pattern classification (2016)
Journal Article
Sartakhti, J., Afrabandpey, H., & Saraee, M. (2017). Simulated annealing least squares twin support vector machine (SA-LSTSVM) for pattern classification. Soft Computing, 21(15), 4361-4373. https://doi.org/10.1007/s00500-016-2067-4

Least squares twin support vector machine (LSTSVM) is a relatively new version of support vector machine (SVM) based on non-parallel twin hyperplanes. Although, LSTSVM is an extremely efficient and fast algorithm for binary classification, its p... Read More about Simulated annealing least squares twin support vector machine (SA-LSTSVM) for pattern classification.