Outputs (28)

Persuasive dialogue understanding: The baselines and negative results (2020)
Journal Article
Chen, H., Ghosal, D., Majumder, N., Hussain, A., & Poria, S. (2021). Persuasive dialogue understanding: The baselines and negative results. Neurocomputing, 431, 47-56. https://doi.org/10.1016/j.neucom.2020.11.040

Persuasion aims at forming one’s opinion and action via a series of persuasive messages containing persuader’s strategies. Due to its potential application in persuasive dialogue systems, the task of persuasive strategy recognition has gained much at... Read More about Persuasive dialogue understanding: The baselines and negative results.

Visual Speech Recognition with Lightweight Psychologically Motivated Gabor Features (2020)
Journal Article
Zhang, X., Xu, Y., Abel, A. K., Smith, L. S., Watt, R., Hussain, A., & Gao, C. (2020). Visual Speech Recognition with Lightweight Psychologically Motivated Gabor Features. Entropy, 22(12), Article 1367. https://doi.org/10.3390/e22121367

Extraction of relevant lip features is of continuing interest in the visual speech domain. Using end-to-end feature extraction can produce good results, but at the cost of the results being difficult for humans to comprehend and relate to. We present... Read More about Visual Speech Recognition with Lightweight Psychologically Motivated Gabor Features.

Big data and IoT-based applications in smart environments: A systematic review (2020)
Journal Article
Hajjaji, Y., Boulila, W., Farah, I. R., Romdhani, I., & Hussain, A. (2021). Big data and IoT-based applications in smart environments: A systematic review. Computer Science Review, 39, Article 100318. https://doi.org/10.1016/j.cosrev.2020.100318

This paper reviews big data and Internet of Things (IoT)-based applications in smart environments. The aim is to identify key areas of application, current trends, data architectures, and ongoing challenges in these fields. To the best of our knowled... Read More about Big data and IoT-based applications in smart environments: A systematic review.

Airport Detection in SAR Images via Salient Line Segment Detector and Edge-Oriented Region Growing (2020)
Journal Article
Tu, J., Gao, F., Sun, J., Hussain, A., & Zhou, H. (2020). Airport Detection in SAR Images via Salient Line Segment Detector and Edge-Oriented Region Growing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 314-326. https://doi.org/10.1109/jstars.2020.3036052

Airport detection in synthetic aperture radar (SAR) images has attracted much concern in the field of remote sensing. Affected by other salient objects with geometrical features similar to those of airports, traditional methods often generate false d... Read More about Airport Detection in SAR Images via Salient Line Segment Detector and Edge-Oriented Region Growing.

ASPIRE - Real noisy audio-visual speech enhancement corpus (2020)
Data
Gogate, M., Dashtipour, K., Adeel, A., & Hussain, A. (2020). ASPIRE - Real noisy audio-visual speech enhancement corpus. [Data]. https://doi.org/10.5281/zenodo.4585619

ASPIRE is a a first of its kind, audiovisual speech corpus recorded in real noisy environment (such as cafe, restaurants) which can be used to support reliable evaluation of multi-modal Speech Filtering technologies. This dataset follows the same sen... Read More about ASPIRE - Real noisy audio-visual speech enhancement corpus.

Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System. (2020)
Presentation / Conference Contribution
Gogate, M., Dashtipour, K., & Hussain, A. (2020, October). Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System. Presented at Interspeech 2020, Shanghai, China

In this paper, we present VIsual Speech In real nOisy eNvironments (VISION), a first of its kind audio-visual (AV) corpus comprising 2500 utterances from 209 speakers, recorded in real noisy environments including social gatherings, streets, cafeteri... Read More about Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System..

A novel approach to stance detection in social media tweets by fusing ranked lists and sentiments (2020)
Journal Article
Al-Ghadir, A. I., Azmi, A. M., & Hussain, A. (2021). A novel approach to stance detection in social media tweets by fusing ranked lists and sentiments. Information Fusion, 67, 29-40. https://doi.org/10.1016/j.inffus.2020.10.003

Stance detection is a relatively new concept in data mining that aims to assign a stance label (favor, against, or none) to a social media post towards a specific pre-determined target. These targets may not be referred to in the post, and may not be... Read More about A novel approach to stance detection in social media tweets by fusing ranked lists and sentiments.

A Novel Intelligent Computational Approach to Model Epidemiological Trends and Assess the Impact of Non-Pharmacological Interventions for COVID-19 (2020)
Journal Article
Ren, J., Yan, Y., Zhao, H., Ma, P., Zabalza, J., Hussain, Z., Luo, S., Dai, Q., Zhao, S., Sheikh, A., Hussain, A., & Li, H. (2020). A Novel Intelligent Computational Approach to Model Epidemiological Trends and Assess the Impact of Non-Pharmacological Interventions for COVID-19. IEEE Journal of Biomedical and Health Informatics, 24(12), 3551-3563. https://doi.org/10.1109/JBHI.2020.3027987

The novel coronavirus disease 2019 (COVID-19) pandemic has led to a worldwide crisis in public health. It is crucial we understand the epidemiological trends and impact of non-pharmacological interventions (NPIs), such as lockdowns for effective mana... Read More about A Novel Intelligent Computational Approach to Model Epidemiological Trends and Assess the Impact of Non-Pharmacological Interventions for COVID-19.

Deep Neural Network Driven Binaural Audio Visual Speech Separation (2020)
Presentation / Conference Contribution
Gogate, M., Dashtipour, K., Bell, P., & Hussain, A. (2020, July). Deep Neural Network Driven Binaural Audio Visual Speech Separation. Presented at 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow

The central auditory pathway exploits the auditory signals and visual information sent by both ears and eyes to segregate speech from multiple competing noise sources and help disambiguate phonological ambiguity. In this study, inspired from this uni... Read More about Deep Neural Network Driven Binaural Audio Visual Speech Separation.

A Novel Approach to Shadow Boundary Detection Based on an Adaptive Direction-Tracking Filter for Brain-Machine Interface Applications (2020)
Journal Article
Ju, Z., Gun, L., Hussain, A., Mahmud, M., & Ieracitano, C. (2020). A Novel Approach to Shadow Boundary Detection Based on an Adaptive Direction-Tracking Filter for Brain-Machine Interface Applications. Applied Sciences, 10(19), Article 6761. https://doi.org/10.3390/app10196761

In this paper, a Brain-Machine Interface (BMI) system is proposed to automatically control the navigation of wheelchairs by detecting the shadows on their route. In this context, a new algorithm to detect shadows in a single image is proposed. Specif... Read More about A Novel Approach to Shadow Boundary Detection Based on an Adaptive Direction-Tracking Filter for Brain-Machine Interface Applications.