All Outputs (304)

Arabic question answering system: a survey (2021)
Journal Article
Alwaneen, T. H., Azmi, A. M., Aboalsamh, H. A., Cambria, E., & Hussain, A. (2022). Arabic question answering system: a survey. Artificial Intelligence Review, 55, 207-253. https://doi.org/10.1007/s10462-021-10031-1

Question answering is a subfield of information retrieval. It is a task of answering a question posted in a natural language. A question answering system (QAS) may be considered a good alternative to search engines that return a set of related docume... Read More about Arabic question answering system: a survey.

Public perception of the fifth generation of cellular networks (5G) on social media (2021)
Journal Article
Dashtipour, K., Taylor, W., Ansari, S., Gogate, M., Zahid, A., Sambo, Y., Hussain, A., Abbasi, Q. H., & Imran, M. A. (2021). Public perception of the fifth generation of cellular networks (5G) on social media. Frontiers in Big Data, 4, Article 640868. htt

With the advancement of social media networks, there are lots of unlabeled reviews available online, therefore it is necessarily to develop automatic tools to classify these types of reviews. To utilize these reviews for user perception, there is a n... Read More about Public perception of the fifth generation of cellular networks (5G) on social media.

Radar Sensing for Activity Classification in Elderly People Exploiting Micro-Doppler Signatures Using Machine Learning (2021)
Journal Article
Taylor, W., Dashtipour, K., Shah, S. A., Hussain, A., Abbasi, Q. H., & Imran, M. A. (2021). Radar Sensing for Activity Classification in Elderly People Exploiting Micro-Doppler Signatures Using Machine Learning. Sensors, 21(11), Article 3881. https://doi.

The health status of an elderly person can be identified by examining the additive effects of aging along with disease linked to it and can lead to ‘unstable incapacity’. This health status is determined by the apparent decline of independence in act... Read More about Radar Sensing for Activity Classification in Elderly People Exploiting Micro-Doppler Signatures Using Machine Learning.

Ten Years of Sentic Computing (2021)
Journal Article
Susanto, Y., Cambria, E., Ng, B. C., & Hussain, A. (2022). Ten Years of Sentic Computing. Cognitive Computation, 14, 5-23. https://doi.org/10.1007/s12559-021-09824-x

Sentic computing is a multi-disciplinary approach to sentiment analysis at the crossroads between affective computing and commonsense computing, which exploits both computer and social sciences to better recognize, interpret, and process opinions and... Read More about Ten Years of Sentic Computing.

Advances in machine translation for sign language: approaches, limitations, and challenges (2021)
Journal Article
Farooq, U., Rahim, M. S. M., Sabir, N., Hussain, A., & Abid, A. (2021). Advances in machine translation for sign language: approaches, limitations, and challenges. Neural Computing and Applications, 33, 14357-14399. https://doi.org/10.1007/s00521-021-0607

Sign languages are used by the deaf community around the globe to communicate with one another. These are gesture-based languages where a deaf person performs gestures using hands and facial expressions. Every gesture represents a word or a phrase in... Read More about Advances in machine translation for sign language: approaches, limitations, and challenges.

Understanding Public Perceptions of COVID-19 Contact Tracing Apps: Artificial Intelligence–Enabled Social Media Analysis (2021)
Journal Article
Cresswell, K., Tahir, A., Sheikh, Z., Hussain, Z., Domínguez Hernández, A., Harrison, E., …Hussain, A. (2021). Understanding Public Perceptions of COVID-19 Contact Tracing Apps: Artificial Intelligence–Enabled Social Media Analysis. Journal of Medic

Background: The emergence of SARS-CoV-2 in late 2019 and its subsequent spread worldwide continues to be a global health crisis. Many governments consider contact tracing of citizens through apps installed on mobile phones as a key mechanism to conta... Read More about Understanding Public Perceptions of COVID-19 Contact Tracing Apps: Artificial Intelligence–Enabled Social Media Analysis.

Sentiment analysis of persian movie reviews using deep learning (2021)
Journal Article
Dashtipour, K., Gogate, M., Adeel, A., Larijani, H., & Hussain, A. (2021). Sentiment analysis of persian movie reviews using deep learning. Entropy, 23(5), Article 596. https://doi.org/10.3390/e23050596

Sentiment analysis aims to automatically classify the subject’s sentiment (e.g., positive, negative, or neutral) towards a particular aspect such as a topic, product, movie, news, etc. Deep learning has recently emerged as a powerful machine learning... Read More about Sentiment analysis of persian movie reviews using deep learning.

A Novel Deep Learning Method for Recognition and Classification of Brain Tumors from MRI images (2021)
Journal Article
Masood, M., Nazir, T., Nawaz, M., Mehmood, A., Rashid, J., Kwon, H., …Hussain, A. (2021). A Novel Deep Learning Method for Recognition and Classification of Brain Tumors from MRI images. Diagnostics, 11(5), Article 744. https://doi.org/10.3390/diagnosti

A brain tumor is an abnormal growth in brain cells that causes damage to various blood vessels and nerves in the human body. An earlier and accurate diagnosis of the brain tumor is of foremost important to avoid future complications. Precise segmenta... Read More about A Novel Deep Learning Method for Recognition and Classification of Brain Tumors from MRI images.

Improving generative adversarial networks with simple latent distributions (2021)
Journal Article
Zhang, S., Huang, K., Qian, Z., Zhang, R., & Hussain, A. (2021). Improving generative adversarial networks with simple latent distributions. Neural Computing and Applications, 33, 13193-13203. https://doi.org/10.1007/s00521-021-05946-3

Generative Adversarial Networks (GANs) have drawn great attention recently since they are the powerful models to generate high-quality images. Although GANs have achieved great success, they usually suffer from unstable training and consequently may... Read More about Improving generative adversarial networks with simple latent distributions.

Does semantics aid syntax? An empirical study on named entity recognition and classification (2021)
Journal Article
Zhong, X., Cambria, E., & Hussain, A. (2022). Does semantics aid syntax? An empirical study on named entity recognition and classification. Neural Computing and Applications, 34, 8373-8384. https://doi.org/10.1007/s00521-021-05949-0

Many researchers jointly model multiple linguistic tasks (e.g., joint modeling of named entity recognition and named entity classification and joint modeling of syntactic parsing and semantic parsing) with an implicit assumption that these individual... Read More about Does semantics aid syntax? An empirical study on named entity recognition and classification.

Artificial intelligence--enabled analysis of public attitudes on facebook and twitter toward covid-19 vaccines in the united kingdom and the united states: Observational study (2021)
Journal Article
Hussain, A., Tahir, A., Hussain, Z., Sheikh, Z., Gogate, M., Dashtipour, K., Ali, A., & Sheikh, A. (2021). Artificial intelligence--enabled analysis of public attitudes on facebook and twitter toward covid-19 vaccines in the united kingdom and the united

Background: Global efforts toward the development and deployment of a vaccine for COVID-19 are rapidly advancing. To achieve herd immunity, widespread administration of vaccines is required, which necessitates significant cooperation from the general... Read More about Artificial intelligence--enabled analysis of public attitudes on facebook and twitter toward covid-19 vaccines in the united kingdom and the united states: Observational study.

A novel domain activation mapping-guided network (DA-GNT) for visual tracking (2021)
Journal Article
Tu, Z., Zhou, A., Gan, C., Jiang, B., Hussain, A., & Luo, B. (2021). A novel domain activation mapping-guided network (DA-GNT) for visual tracking. Neurocomputing, 449, 443-454. https://doi.org/10.1016/j.neucom.2021.03.056

Conventional convolution neural network (CNN)-based visual trackers are easily influenced by too much background information in candidate samples. Further, extreme imbalance of foreground and background samples has a negative impact on training the c... Read More about A novel domain activation mapping-guided network (DA-GNT) for visual tracking.

Learning Polar Encodings for Arbitrary-Oriented Ship Detection in SAR Images (2021)
Journal Article
He, Y., Gao, F., Wang, J., Hussain, A., Yang, E., & Zhou, H. (2021). Learning Polar Encodings for Arbitrary-Oriented Ship Detection in SAR Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 3846-3859. https://doi

Common horizontal bounding box-based methods are not capable of accurately locating slender ship targets with arbitrary orientations in synthetic aperture radar (SAR) images. Therefore, in recent years, methods based on oriented bounding box (OBB) ha... Read More about Learning Polar Encodings for Arbitrary-Oriented Ship Detection in SAR Images.

A Novel Coupled Reaction-Diffusion System for Explainable Gene Expression Profiling (2021)
Journal Article
Farouq, M. W., Boulila, W., Hussain, Z., Rashid, A., Shah, M., Hussain, S., …Hussain, A. (2021). A Novel Coupled Reaction-Diffusion System for Explainable Gene Expression Profiling. Sensors, 21(6), Article 2190. https://doi.org/10.3390/s21062190

Machine learning (ML)-based algorithms are playing an important role in cancer diagnosis and are increasingly being used to aid clinical decision-making. However, these commonly operate as ‘black boxes’ and it is unclear how decisions are derived. Re... Read More about A Novel Coupled Reaction-Diffusion System for Explainable Gene Expression Profiling.

Novel deep convolutional neural network-based contextual recognition of Arabic handwritten scripts (2021)
Journal Article
Ahmed, R., Gogate, M., Tahir, A., Dashtipour, K., Al-Tamimi, B., Hawalah, A., El-Affendi, M. A., & Hussain, A. (2021). Novel deep convolutional neural network-based contextual recognition of Arabic handwritten scripts. Entropy, 23(3), Article 340. https:/

Offline Arabic Handwriting Recognition (OAHR) has recently become instrumental in the areas of pattern recognition and image processing due to its application in several fields, such as office automation and document processing. However, OAHR continu... Read More about Novel deep convolutional neural network-based contextual recognition of Arabic handwritten scripts.

A novel explainable machine learning approach for EEG-based brain-computer interface systems (2021)
Journal Article
Ieracitano, C., Mammone, N., Hussain, A., & Morabito, F. C. (2022). A novel explainable machine learning approach for EEG-based brain-computer interface systems. Neural Computing and Applications, 34, 11347-11360. https://doi.org/10.1007/s00521-020-0562

Electroencephalographic (EEG) recordings can be of great help in decoding the open/close hand’s motion preparation. To this end, cortical EEG source signals in the motor cortex (evaluated in the 1-s window preceding movement onset) are extracted by s... Read More about A novel explainable machine learning approach for EEG-based brain-computer interface systems.

Discriminative Dictionary Design for Action Classification in Still Images and Videos (2021)
Journal Article
Roy, A., Banerjee, B., Hussain, A., & Poria, S. (2021). Discriminative Dictionary Design for Action Classification in Still Images and Videos. Cognitive Computation, 13, 698-708. https://doi.org/10.1007/s12559-021-09851-8

In this paper, we address the problem of action recognition from still images and videos. Traditional local features such as SIFT and STIP invariably pose two potential problems: 1) they are not evenly distributed in different entities of a given cat... Read More about Discriminative Dictionary Design for Action Classification in Still Images and Videos.

A novel context-aware multimodal framework for persian sentiment analysis (2021)
Journal Article
Dashtipour, K., Gogate, M., Cambria, E., & Hussain, A. (2021). A novel context-aware multimodal framework for persian sentiment analysis. Neurocomputing, 457, 377-388. https://doi.org/10.1016/j.neucom.2021.02.020

Most recent works on sentiment analysis have exploited the text modality. However, millions of hours of video recordings posted on social media platforms everyday hold vital unstructured information that can be exploited to more effectively gauge pub... Read More about A novel context-aware multimodal framework for persian sentiment analysis.

A semi-supervised approach for sentiment analysis of arab (ic+ izi) messages: Application to the algerian dialect (2021)
Journal Article
Guellil, I., Adeel, A., Azouaou, F., Benali, F., Hachani, A., Dashtipour, K., …Hussain, A. (2021). A semi-supervised approach for sentiment analysis of arab (ic+ izi) messages: Application to the algerian dialect. SN Computer Science, 2, Article 118. ht

In this paper, we propose a semi-supervised approach for sentiment analysis of Arabic and its dialects. This approach is based on a sentiment corpus, constructed automatically and reviewed manually by Algerian dialect native speakers. This approach c... Read More about A semi-supervised approach for sentiment analysis of arab (ic+ izi) messages: Application to the algerian dialect.

A Multipath Fusion Strategy Based Single Shot Detector (2021)
Journal Article
Qu, S., Huang, K., Hussain, A., & Goulermas, Y. (2021). A Multipath Fusion Strategy Based Single Shot Detector. Sensors, 21(4), Article 1360. https://doi.org/10.3390/s21041360

Object detection has wide applications in intelligent systems and sensor applications. Compared with two stage detectors, recent one stage counterparts are capable of running more efficiently with comparable accuracy, which satisfy the requirement of... Read More about A Multipath Fusion Strategy Based Single Shot Detector.