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Editorial: Physiological computing of social cognition, volume II (2023)
Journal Article
Fernández-Caballero, A., Hussain, A., Latorre, J. M., Martínez-Rodrigo, A., Rodriguez-Jimenez, R., & Fernández-Sotos, P. (2023). Editorial: Physiological computing of social cognition, volume II. Frontiers in Human Neuroscience, 17, Article 1152291. ht

[Abstract unavailable.]

Randomized block-coordinate adaptive algorithms for nonconvex optimization problems (2023)
Journal Article
Zhou, Y., Huang, K., Li, J., Cheng, C., Wang, X., Hussian, A., & Liu, X. (2023). Randomized block-coordinate adaptive algorithms for nonconvex optimization problems. Engineering Applications of Artificial Intelligence, 121, Article 105968. https://doi.org

Nonconvex optimization problems have always been one focus in deep learning, in which many fast adaptive algorithms based on momentum are applied. However, the full gradient computation of high-dimensional feature vector in the above tasks become pro... Read More about Randomized block-coordinate adaptive algorithms for nonconvex optimization problems.

A Novel Hierarchical Extreme Machine-Learning-Based Approach for Linear Attenuation Coefficient Forecasting (2023)
Journal Article
Varone, G., Ieracitano, C., Çiftçioğlu, A. Ö., Hussain, T., Gogate, M., Dashtipour, K., Al-Tamimi, B. N., Almoamari, H., Akkurt, I., & Hussain, A. (2023). A Novel Hierarchical Extreme Machine-Learning-Based Approach for Linear Attenuation Coefficient

The development of reinforced polymer composite materials has had a significant influence on the challenging problem of shielding against high-energy photons, particularly X-rays and γ-rays in industrial and healthcare facilities. Heavy materials’ sh... Read More about A Novel Hierarchical Extreme Machine-Learning-Based Approach for Linear Attenuation Coefficient Forecasting.

AVSE Challenge: Audio-Visual Speech Enhancement Challenge (2023)
Presentation / Conference Contribution
Aldana Blanco, A. L., Valentini-Botinhao, C., Klejch, O., Gogate, M., Dashtipour, K., Hussain, A., & Bell, P. (2023, January). AVSE Challenge: Audio-Visual Speech Enhancement Challenge. Presented at 2022 IEEE Spoken Language Technology Workshop (SLT), Doh

Audio-visual speech enhancement is the task of improving the quality of a speech signal when video of the speaker is available. It opens-up the opportunity of improving speech intelligibility in adverse listening scenarios that are currently too chal... Read More about AVSE Challenge: Audio-Visual Speech Enhancement Challenge.

Panchromatic and multispectral image fusion for remote sensing and earth observation: Concepts, taxonomy, literature review, evaluation methodologies and challenges ahead (2023)
Journal Article
Zhang, K., Zhang, F., Wan, W., Yu, H., Sun, J., Del Ser, J., …Hussain, A. (2023). Panchromatic and multispectral image fusion for remote sensing and earth observation: Concepts, taxonomy, literature review, evaluation methodologies and challenges ahead.

Panchromatic and multispectral image fusion, termed pan-sharpening, is to merge the spatial and spectral information of the source images into a fused one, which has a higher spatial and spectral resolution and is more reliable for downstream tasks c... Read More about Panchromatic and multispectral image fusion for remote sensing and earth observation: Concepts, taxonomy, literature review, evaluation methodologies and challenges ahead.

Diverse features discovery transformer for pedestrian attribute recognition (2022)
Journal Article
Zheng, A., Wang, H., Wang, J., Huang, H., He, R., & Hussain, A. (2023). Diverse features discovery transformer for pedestrian attribute recognition. Engineering Applications of Artificial Intelligence, 119, Article 105708. https://doi.org/10.1016/j.engapp

Recently, Swin Transformer has been widely explored as a general backbone for computer vision, which helps to improve the performance of vision tasks due to the ability to establish associations for long-range dependencies of different spatial locati... Read More about Diverse features discovery transformer for pedestrian attribute recognition.

A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids (2022)
Presentation / Conference Contribution
Bishnu, A., Gupta, A., Gogate, M., Dashtipour, K., Adeel, A., Hussain, A., Sellathurai, M., & Ratnarajah, T. (2022, October). A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids. Presented at 2022 IEEE Intern

In this paper, we design a first of its kind transceiver (PHY layer) prototype for cloud-based audio-visual (AV) speech enhancement (SE) complying with high data rate and low latency requirements of future multimodal hearing assistive technology. The... Read More about A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids.

Multimodal salient object detection via adversarial learning with collaborative generator (2022)
Journal Article
Tu, Z., Yang, W., Wang, K., Hussain, A., Luo, B., & Li, C. (2023). Multimodal salient object detection via adversarial learning with collaborative generator. Engineering Applications of Artificial Intelligence, 119, Article 105707. https://doi.org/10.1016

Multimodal salient object detection(MSOD), which utilizes multimodal information (e.g., RGB image and thermal infrared or depth image) to detect common salient objects, has received much attention recently. Different modalities reflect different appe... Read More about Multimodal salient object detection via adversarial learning with collaborative generator.

A novel approach of many-objective particle swarm optimization with cooperative agents based on an inverted generational distance indicator (2022)
Journal Article
Kouka, N., BenSaid, F., Fdhila, R., Fourati, R., Hussain, A., & Alimi, A. M. (2023). A novel approach of many-objective particle swarm optimization with cooperative agents based on an inverted generational distance indicator. Information Sciences, 623, 22

Most evolutionary algorithms, including particle swarm optimization (PSO), use Pareto dominance as a major selection criterion and face significant challenges when dealing with many-objective problems. To tackle this issue, this paper proposes a nove... Read More about A novel approach of many-objective particle swarm optimization with cooperative agents based on an inverted generational distance indicator.

Towards Simple and Accurate Human Pose Estimation With Stair Network (2022)
Journal Article
Jiang, C., Huang, K., Zhang, S., Wang, X., Xiao, J., Niu, Z., & Hussain, A. (2023). Towards Simple and Accurate Human Pose Estimation With Stair Network. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(3), 805-817. https://doi.org/10

In this paper, we focus on tackling the precise keypoint coordinates regression task. Most existing approaches adopt complicated networks with a large number of parameters, leading to a heavy model with poor cost-effectiveness in practice. To overcom... Read More about Towards Simple and Accurate Human Pose Estimation With Stair Network.

Canonical cortical graph neural networks and its application for speech enhancement in audio-visual hearing aids (2022)
Journal Article
Passos, L. A., Papa, J. P., Hussain, A., & Adeel, A. (2023). Canonical cortical graph neural networks and its application for speech enhancement in audio-visual hearing aids. Neurocomputing, 527, 196-203. https://doi.org/10.1016/j.neucom.2022.11.081

Despite the recent success of machine learning algorithms, most models face drawbacks when considering more complex tasks requiring interaction between different sources, such as multimodal input data and logical time sequences. On the other hand, th... Read More about Canonical cortical graph neural networks and its application for speech enhancement in audio-visual hearing aids.

Ellipse Encoding for Arbitrary-Oriented SAR Ship Detection Based on Dynamic Key Points (2022)
Journal Article
Gao, F., Huo, Y., Sun, J., Yu, T., Hussain, A., & Zhou, H. (2022). Ellipse Encoding for Arbitrary-Oriented SAR Ship Detection Based on Dynamic Key Points. IEEE Transactions on Geoscience and Remote Sensing, 60, Article 5240528. https://doi.org/10.1109/tgr

In recent years, there has been growing interest in developing oriented bounding box (OBB)-based deep learning approaches to detect arbitrary-oriented ship targets in synthetic aperture radar (SAR) images. However, most existing OBB-based detection m... Read More about Ellipse Encoding for Arbitrary-Oriented SAR Ship Detection Based on Dynamic Key Points.

Fusing external knowledge resources for natural language understanding techniques: A survey (2022)
Journal Article
Wang, Y., Wang, W., Chen, Q., Huang, K., Nguyen, A., De, S., & Hussain, A. (2023). Fusing external knowledge resources for natural language understanding techniques: A survey. Information Fusion, 92, 190-204. https://doi.org/10.1016/j.inffus.2022.11.025

Knowledge resources, e.g. knowledge graphs, which formally represent essential semantics and information for logic inference and reasoning, can compensate for the unawareness nature of many natural language processing techniques based on deep neural... Read More about Fusing external knowledge resources for natural language understanding techniques: A survey.

A robust deep learning approach for tomato plant leaf disease localization and classification (2022)
Journal Article
Nawaz, M., Nazir, T., Javed, A., Masood, M., Rashid, J., Kim, J., & Hussain, A. (2022). A robust deep learning approach for tomato plant leaf disease localization and classification. Scientific Reports, 12(1), Article 18568. https://doi.org/10.1038/s41598

Tomato plants' disease detection and classification at the earliest stage can save the farmers from expensive crop sprays and can assist in increasing the food quantity. Although, extensive work has been presented by the researcher for the tomato pla... Read More about A robust deep learning approach for tomato plant leaf disease localization and classification.

A Trimodel SAR Semisupervised Recognition Method Based on Attention-Augmented Convolutional Networks (2022)
Journal Article
Yan, S., Zhang, Y., Gao, F., Sun, J., Hussain, A., & Zhou, H. (2022). A Trimodel SAR Semisupervised Recognition Method Based on Attention-Augmented Convolutional Networks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1

Semisupervised learning in synthetic aperture radars (SARs) is one of the research hotspots in the field of radar image automatic target recognition. It can efficiently deal with challenging environments where there are insufficient labeled samples a... Read More about A Trimodel SAR Semisupervised Recognition Method Based on Attention-Augmented Convolutional Networks.

PointGS: Bridging and fusing geometric and semantic space for 3D point cloud analysis (2022)
Journal Article
Jiang, C., Huang, K., Wu, J., Wang, X., Xiao, J., & Hussain, A. (2023). PointGS: Bridging and fusing geometric and semantic space for 3D point cloud analysis. Information Fusion, 91, 316-326. https://doi.org/10.1016/j.inffus.2022.10.016

Directly processing 3D point cloud data becomes dominant in classification and segmentation tasks. Present mainstream point based methods usually focus on learning in either geometric space ( PointNet++) or semantic space ( DGCNN). Owing to the irreg... Read More about PointGS: Bridging and fusing geometric and semantic space for 3D point cloud analysis.

WikiDes: A Wikipedia-based dataset for generating short descriptions from paragraphs (2022)
Journal Article
Ta, H. T., Rahman, A. B. S., Majumder, N., Hussain, A., Najjar, L., Howard, N., …Gelbukh, A. (2023). WikiDes: A Wikipedia-based dataset for generating short descriptions from paragraphs. Information Fusion, 90, 265-282. https://doi.org/10.1016/j.inffus.

As free online encyclopedias with massive volumes of content, Wikipedia and Wikidata are key to many Natural Language Processing (NLP) tasks, such as information retrieval, knowledge base building, machine translation, text classification, and text s... Read More about WikiDes: A Wikipedia-based dataset for generating short descriptions from paragraphs.

Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions (2022)
Journal Article
Gandhi, A., Adhvaryu, K., Poria, S., Cambria, E., & Hussain, A. (2023). Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions. Information Fusion, 91, 424-444. ht

Sentiment analysis (SA) has gained much traction In the field of artificial intelligence (AI) and natural language processing (NLP). There is growing demand to automate analysis of user sentiment towards products or services. Opinions are increasingl... Read More about Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions.

Towards real-time privacy-preserving audio-visual speech enhancement (2022)
Presentation / Conference Contribution
Gogate, M., Dashtipour, K., & Hussain, A. (2022, September). Towards real-time privacy-preserving audio-visual speech enhancement. Presented at 2nd Symposium on Security and Privacy in Speech Communication, Incheon, Korea

Human auditory cortex in everyday noisy situations is known to exploit aural and visual cues that are contextually combined by the brain’s multi-level integration strategies to selectively suppress the background noise and focus on the target speaker... Read More about Towards real-time privacy-preserving audio-visual speech enhancement.

A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling (2022)
Journal Article
Comminiello, D., Nezamdoust, A., Scardapane, S., Scarpiniti, M., Hussain, A., & Uncini, A. (2023). A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling. IEEE Transactions on Systems, Man and Cybernetics: Systems, 53(3), 1384-1396. https

Nonlinear models are known to provide excellent performance in real-world applications that often operate in nonideal conditions. However, such applications often require online processing to be performed with limited computational resources. To addr... Read More about A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling.