All Outputs (479)

Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection (2018)
Presentation / Conference Contribution
Ieracitano, C., Adeel, A., Gogate, M., Dashtipour, K., Morabito, F., Larijani, H., …Hussain, A. (2018). Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection. . https://doi.org/10.1007/978-3-030-00563-4_74

Attackers have developed ever more sophisticated and intelligent ways to hack information and communication technology (ICT) systems. The extent of damage an individual hacker can carry out upon infiltrating a system is well understood. A potentially... Read More about Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection.

SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis (2018)
Presentation / Conference Contribution
Guellil, I., Adeel, A., Azouaou, F., & Hussain, A. (2018). SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis. . https://doi.org/10.1007/978-3-030-00563-4_54

Data annotation is an important but time-consuming and costly procedure. To sort a text into two classes, the very first thing we need is a good annotation guideline, establishing what is required to qualify for each class. In the literature, the dif... Read More about SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis.

Saliency Detection via Bidirectional Absorbing Markov Chain (2018)
Presentation / Conference Contribution
Jiang, F., Kong, B., Adeel, A., Xiao, Y., & Hussain, A. (2018). Saliency Detection via Bidirectional Absorbing Markov Chain. . https://doi.org/10.1007/978-3-030-00563-4_48

Traditional saliency detection via Markov chain only consider boundaries nodes. However, in addition to boundaries cues, background prior and foreground prior cues play a complementary role to enhance saliency detection. In this paper, we propose an... Read More about Saliency Detection via Bidirectional Absorbing Markov Chain.

Exploiting Deep Learning for Persian Sentiment Analysis (2018)
Presentation / Conference Contribution
Dashtipour, K., Gogate, M., Adeel, A., Ieracitano, C., Larijani, H., & Hussain, A. (2018). Exploiting Deep Learning for Persian Sentiment Analysis. In Advances in Brain Inspired Cognitive Systems (597-604). https://doi.org/10.1007/978-3-030-00563-4_58

The rise of social media is enabling people to freely express their opinions about products and services. The aim of sentiment analysis is to automatically determine subject’s sentiment (e.g., positive, negative, or neutral) towards a particular aspe... Read More about Exploiting Deep Learning for Persian Sentiment Analysis.

Comparison of Sentiment Analysis Approaches Using Modern Arabic and Sudanese Dialect (2018)
Presentation / Conference Contribution
Hussien, I., Dashtipour, K., & Hussain, A. (2018). Comparison of Sentiment Analysis Approaches Using Modern Arabic and Sudanese Dialect. In Advances in Brain Inspired Cognitive Systems (615-624). https://doi.org/10.1007/978-3-030-00563-4_60

Sentiment analysis mainly focused on the automatic recognition of opinions’ polarity, as positive or negative. Nowadays, sentiment analysis is replacing the web-based and traditional survey methods commonly conducted by companies for finding the publ... Read More about Comparison of Sentiment Analysis Approaches Using Modern Arabic and Sudanese Dialect.

A Semi-supervised Corpus Annotation for Saudi Sentiment Analysis Using Twitter (2018)
Journal Article
Alqarafi, A., Adeel, A., Hawalah, A., Swingler, K., & Hussain, A. (2018). A Semi-supervised Corpus Annotation for Saudi Sentiment Analysis Using Twitter. Lecture Notes in Computer Science, 589-596. https://doi.org/10.1007/978-3-030-00563-4_57

In the literature, limited work has been conducted to develop sentiment resources for Saudi dialect. The lack of resources such as dialectical lexicons and corpora are some of the major bottlenecks to the successful development of Arabic sentiment an... Read More about A Semi-supervised Corpus Annotation for Saudi Sentiment Analysis Using Twitter.

A Novel Semi-supervised Classification Method Based on Class Certainty of Samples (2018)
Presentation / Conference Contribution
Gao, F., Yue, Z., Xiong, Q., Wang, J., Yang, E., & Hussain, A. (2018). A Novel Semi-supervised Classification Method Based on Class Certainty of Samples. . https://doi.org/10.1007/978-3-030-00563-4_30

The traditional classification method based on supervised learning classifies remote sensing (RS) images by using sufficient labelled samples. However, the number of labelled samples is limited due to the expensive and time-consuming collection. To e... Read More about A Novel Semi-supervised Classification Method Based on Class Certainty of Samples.

A Convolutional Neural Network approach for classification of dementia stages based on 2D-spectral representation of EEG recordings (2018)
Journal Article
Ieracitano, C., Mammone, N., Bramanti, A., Hussain, A., & Morabito, F. (2019). A Convolutional Neural Network approach for classification of dementia stages based on 2D-spectral representation of EEG recordings. Neurocomputing, 323, 96-107. https://doi.or

A data-driven machine deep learning approach is proposed for differentiating subjects with Alzheimer’s Disease (AD), Mild Cognitive Impairment (MCI) and Healthy Control (HC), by only analyzing noninvasive scalp EEG recordings. The methodology here pr... Read More about A Convolutional Neural Network approach for classification of dementia stages based on 2D-spectral representation of EEG recordings.

Cross-modality interactive attention network for multispectral pedestrian detection (2018)
Journal Article
Zhang, L., Liu, Z., Zhang, S., Yang, X., Qiao, H., Huang, K., & Hussain, A. (2019). Cross-modality interactive attention network for multispectral pedestrian detection. Information Fusion, 50, 20-29. https://doi.org/10.1016/j.inffus.2018.09.015

Multispectral pedestrian detection is an emerging solution with great promise in many around-the-clock applications, such as automotive driving and security surveillance. To exploit the complementary nature and remedy contradictory appearance between... Read More about Cross-modality interactive attention network for multispectral pedestrian detection.

A Survey on the Role of Wireless Sensor Networks and IoT in Disaster Management (2018)
Book Chapter
Adeel, A., Gogate, M., Farooq, S., Ieracitano, C., Dashtipour, K., Larijani, H., & Hussain, A. (2019). A Survey on the Role of Wireless Sensor Networks and IoT in Disaster Management. In T. S. Durrani, W. Wang, & S. M. Forbes (Eds.), Geological Disaster M

Extreme events and disasters resulting from climate change or other ecological factors are difficult to predict and manage. Current limitations of state-of-the-art approaches to disaster prediction and management could be addressed by adopting new un... Read More about A Survey on the Role of Wireless Sensor Networks and IoT in Disaster Management.

Towards workload-aware cloud resource provisioning using a multi-controller fuzzy switching approach (2018)
Journal Article
Ullah, A., Li, J., & Hussain, A. (2018). Towards workload-aware cloud resource provisioning using a multi-controller fuzzy switching approach. International Journal of High Performance Computing and Networking, 12(1), 13-25. https://doi.org/10.1504/IJHPCN

Elasticity enables cloud customers to enrich their applications to dynamically adjust underlying cloud resources. Over the past, a plethora of techniques have been introduced to implement elasticity. Control theory is one such technique that offers a... Read More about Towards workload-aware cloud resource provisioning using a multi-controller fuzzy switching approach.

Accelerating Infinite Ensemble of Clustering by Pivot Features (2018)
Journal Article
Jin, X., Xie, G., Huang, K., & Hussain, A. (2018). Accelerating Infinite Ensemble of Clustering by Pivot Features. Cognitive Computation, 10(6), 1042-1050. https://doi.org/10.1007/s12559-018-9583-8

The infinite ensemble clustering (IEC) incorporates both ensemble clustering and representation learning by fusing infinite basic partitions and shows appealing performance in the unsupervised context. However, it needs to solve the linear equation s... Read More about Accelerating Infinite Ensemble of Clustering by Pivot Features.

A comparison of two methods of using a serious game for teaching marine ecology in a university setting (2018)
Journal Article
Ameerbakhsh, O., Maharaj, S., Hussain, A., & McAdam, B. (2019). A comparison of two methods of using a serious game for teaching marine ecology in a university setting. International Journal of Human-Computer Studies, 127, 181-189. https://doi.org/10.1016

There is increasing interest in the use of serious games in STEM education. Interactive simulations and serious games can be used by students to explore systems where it would be impractical or unethical to perform real world studies or experiments.... Read More about A comparison of two methods of using a serious game for teaching marine ecology in a university setting.

A New Algorithm of SAR Image Target Recognition Based on Improved Deep Convolutional Neural Network (2018)
Journal Article
Gao, F., Huang, T., Sun, J., Wang, J., Hussain, A., & Yang, E. (2018). A New Algorithm of SAR Image Target Recognition Based on Improved Deep Convolutional Neural Network. Cognitive Computation, 1-16. https://doi.org/10.1007/s12559-018-9563-z

In an attempt to exploit the automatic feature extraction ability of biologically-inspired deep learning models, and enhance the learning of target features, we propose a novel deep learning algorithm. This is based on a deep convolutional neural net... Read More about A New Algorithm of SAR Image Target Recognition Based on Improved Deep Convolutional Neural Network.

Clinical Decision Support Systems: A Visual Survey (2018)
Journal Article
Farooq, K., Khan, B. S., Niazi, M. A., Leslie, S. J., & Hussain, A. (2018). Clinical Decision Support Systems: A Visual Survey. Informatica, 42(4), 485-505. https://doi.org/10.31449/inf.v42i4.1571

Clinical Decision Support Systems (CDSS) form an important area of research. In spite of its importance, it is difficult for researchers to evaluate the domain primarily because of a considerable spread of relevant literature in interdisciplinary dom... Read More about Clinical Decision Support Systems: A Visual Survey.

Relation Extraction of Medical Concepts Using Categorization and Sentiment Analysis (2018)
Journal Article
Mondal, A., Cambria, E., Das, D., Hussain, A., & Bandyopadhyay, S. (2018). Relation Extraction of Medical Concepts Using Categorization and Sentiment Analysis. Cognitive Computation, 10(4), 670-685. https://doi.org/10.1007/s12559-018-9567-8

In healthcare services, information extraction is the key to understand any corpus-based knowledge. The process becomes laborious when the annotation is done manually for the availability of a large number of text corpora. Hence, future automated ext... Read More about Relation Extraction of Medical Concepts Using Categorization and Sentiment Analysis.

A comparative study of Persian sentiment analysis based on different feature combinations (2018)
Presentation / Conference Contribution
Dashtipour, K., Gogate, M., Adeel, A., Hussain, A., Alqarafi, A., & Durrani, T. (2017, July). A comparative study of Persian sentiment analysis based on different feature combinations. Presented at International Conference in Communications, Signal Proces

In recent years, the use of internet and correspondingly the number of online reviews, comments and opinions have increased significantly. It is indeed very difficult for humans to read these opinions and classify them accurately. Consequently, there... Read More about A comparative study of Persian sentiment analysis based on different feature combinations.

Toward's Arabic multi-modal sentiment analysis (2018)
Presentation / Conference Contribution
Alqarafi, A., Adeel, A., Gogate, M., Dashitpour, K., Hussain, A., & Durrani, T. (2019). Toward's Arabic multi-modal sentiment analysis. . https://doi.org/10.1007/978-981-10-6571-2_290

In everyday life, people use internet to express and share opinions, facts, and sentiments about products and services. In addition, social media applications such as Facebook, Twitter, WhatsApp, Snapchat etc., have become important information shari... Read More about Toward's Arabic multi-modal sentiment analysis.

A new two-layer mixture of factor analyzers with joint factor loading model for the classification of small dataset problems (2018)
Journal Article
Yang, X., Huang, K., Zhang, R., Goulermas, J., & Hussain, A. (2018). A new two-layer mixture of factor analyzers with joint factor loading model for the classification of small dataset problems. Neurocomputing, 312, 352-363. https://doi.org/10.1016/j.neuc

Dimensionality Reduction (DR) is a fundamental topic of pattern classification and machine learning. For classification tasks, DR is typically employed as a pre-processing step, succeeded by an independent classifier training stage. However, such ind... Read More about A new two-layer mixture of factor analyzers with joint factor loading model for the classification of small dataset problems.

A control theoretical view of cloud elasticity: taxonomy, survey and challenges (2018)
Journal Article
Ullah, A., Li, J., Shen, Y., & Hussain, A. (2018). A control theoretical view of cloud elasticity: taxonomy, survey and challenges. Cluster Computing, 21(4), 1735-1764. https://doi.org/10.1007/s10586-018-2807-6

The lucrative features of cloud computing such as pay-as-you-go pricing model and dynamic resource provisioning (elasticity) attract clients to host their applications over the cloud to save up-front capital expenditure and to reduce the operational... Read More about A control theoretical view of cloud elasticity: taxonomy, survey and challenges.