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All Outputs (310)

Impact of the Covid-19 pandemic on audiology service delivery: Observational study of the role of social media in patient communication (2024)
Journal Article
Hussain, A., Hussain, Z., Gogate, M., Dashtipour, K., Ng, D., Riaz, M. S., …Hussain, A. (2024). Impact of the Covid-19 pandemic on audiology service delivery: Observational study of the role of social media in patient communication. PLOS ONE, 19(4), Art

The Covid-19 pandemic has highlighted an era in hearing health care that necessitates a comprehensive rethinking of audiology service delivery. There has been a significant increase in the number of individuals with hearing loss who seek information... Read More about Impact of the Covid-19 pandemic on audiology service delivery: Observational study of the role of social media in patient communication.

Graph learning with label attention and hyperbolic embedding for temporal event prediction in healthcare (2024)
Journal Article
Naseem, U., Thapa, S., Zhang, Q., Wang, S., Rashid, J., Hu, L., & Hussain, A. (2024). Graph learning with label attention and hyperbolic embedding for temporal event prediction in healthcare. Neurocomputing, 592, Article 127736. https://doi.org/10.1016/j.

The digitization of healthcare systems has led to the proliferation of electronic health records (EHRs), serving as comprehensive repositories of patient information. However, the vast volume and complexity of EHR data present challenges in extractin... Read More about Graph learning with label attention and hyperbolic embedding for temporal event prediction in healthcare.

Generative AI for Consumer Electronics: Enhancing User Experience with Cognitive and Semantic Computing (2024)
Journal Article
Chamola, V., Sai, S., Sai, R., Hussain, A., & Sikdar, B. (online). Generative AI for Consumer Electronics: Enhancing User Experience with Cognitive and Semantic Computing. IEEE Consumer Electronics Magazine, https://doi.org/10.1109/mce.2024.3387049

Generative Artificial Intelligence(GAI) models such as ChatGPT , DALL-E , and the recently introduced Gemini have attracted considerable interest in both business and academia because of their capacity to produce material in response to human inputs.... Read More about Generative AI for Consumer Electronics: Enhancing User Experience with Cognitive and Semantic Computing.

Overtaking Mechanisms Based on Augmented Intelligence for Autonomous Driving: Datasets, Methods, and Challenges (2024)
Journal Article
Chamola, V., Chougule, A., Sam, A., Hussain, A., & Yu, F. R. (2024). Overtaking Mechanisms Based on Augmented Intelligence for Autonomous Driving: Datasets, Methods, and Challenges. IEEE Internet of Things, 11(10), 17911-17933. https://doi.org/10.1109/jio

The field of autonomous driving research has made significant strides towards achieving full automation, endowing vehicles with self-awareness and independent decision-making. However, integrating automation into vehicular operations presents formida... Read More about Overtaking Mechanisms Based on Augmented Intelligence for Autonomous Driving: Datasets, Methods, and Challenges.

Application of machine learning in predicting frailty syndrome in patients with heart failure (2024)
Journal Article
Szczepanowski, R., Uchmanowicz, I., Pasieczna-Dixit, A. H., Sobecki, J., Katarzyniak, R., Kołaczek, G., …Kahsin, A. (2024). Application of machine learning in predicting frailty syndrome in patients with heart failure. Advances in Clinical and Experime

Prevention and diagnosis of frailty syndrome (FS) in patients with heart failure (HF) require innovative systems to help medical personnel tailor and optimize their treatment and care. Traditional methods of diagnosing FS in patients could be more sa... Read More about Application of machine learning in predicting frailty syndrome in patients with heart failure.

Opto-electrochemical variation with gel polymer electrolytes in transparent electrochemical capacitors for ionotronics (2024)
Journal Article
Kumar, C., Sebastian, A. K., Markapudi, P. R., Beg, M., Sundaram, S., Hussain, A., & Manjakkal, L. (2024). Opto-electrochemical variation with gel polymer electrolytes in transparent electrochemical capacitors for ionotronics. Applied Physics Letters, 124

Advanced flexible ionotronic devices have found excellent applications in the next generation of electronic skin (e-skin) development for smart wearables, robotics, and prosthesis. In this work, we developed transparent ionotronic-based flexible elec... Read More about Opto-electrochemical variation with gel polymer electrolytes in transparent electrochemical capacitors for ionotronics.

Hate speech detection: A comprehensive review of recent works (2024)
Journal Article
Gandhi, A., Ahir, P., Adhvaryu, K., Shah, P., Lohiya, R., Cambria, E., Poria, S., & Hussain, A. (online). Hate speech detection: A comprehensive review of recent works. Expert Systems, https://doi.org/10.1111/exsy.13562

There has been surge in the usage of Internet as well as social media platforms which has led to rise in online hate speech targeted on individual or group. In the recent years, hate speech has resulted in one of the challenging problems that can unf... Read More about Hate speech detection: A comprehensive review of recent works.

BBox-Free SAR Ship Instance Segmentation Method Based on Gaussian Heatmap (2024)
Journal Article
Gao, F., Zhong, F., Sun, J., Hussain, A., & Zhou, H. (2024). BBox-Free SAR Ship Instance Segmentation Method Based on Gaussian Heatmap. IEEE Transactions on Geoscience and Remote Sensing, 62, Article 5206218. https://doi.org/10.1109/tgrs.2024.3369614

Recently, deep learning methods have been widely adopted for ship detection in synthetic aperture radar (SAR) images. However, many of the existing methods miss adjacent ship instances when detecting densely arranged ship targets in inshore scenes. B... Read More about BBox-Free SAR Ship Instance Segmentation Method Based on Gaussian Heatmap.

A novel generative adversarial network‐based super‐resolution approach for face recognition (2024)
Journal Article
Chougule, A., Kolte, S., Chamola, V., & Hussain, A. (online). A novel generative adversarial network‐based super‐resolution approach for face recognition. Expert Systems, https://doi.org/10.1111/exsy.13564

Face recognition is an essential feature required for a range of computer vision applications such as security, attendance systems, emotion detection, airport check-in, and many others. The super-resolution of subject images is an important and chall... Read More about A novel generative adversarial network‐based super‐resolution approach for face recognition.

Robust Real-time Audio-Visual Speech Enhancement based on DNN and GAN (2024)
Journal Article
Gogate, M., Dashtipour, K., & Hussain, A. (in press). Robust Real-time Audio-Visual Speech Enhancement based on DNN and GAN. IEEE Transactions on Artificial Intelligence, https://doi.org/10.1109/tai.2024.3366141

The human auditory cortex contextually integrates audio-visual (AV) cues to better understand speech in a cocktail party situation. Recent studies have shown that AV speech enhancement (SE) models can significantly improve speech quality and intellig... Read More about Robust Real-time Audio-Visual Speech Enhancement based on DNN and GAN.

STIDNet: Identity-Aware Face Forgery Detection with Spatiotemporal Knowledge Distillation (2024)
Journal Article
Fang, M., Yu, L., Xie, H., Tan, Q., Tan, Z., Hussain, A., Wang, Z., Li, J., & Tian, Z. (online). STIDNet: Identity-Aware Face Forgery Detection with Spatiotemporal Knowledge Distillation. IEEE Transactions on Computational Social Systems, https://doi.org/

The impressive development of facial manipulation techniques has raised severe public concerns. Identity-aware methods, especially suitable for protecting celebrities, are seen as one of promising face forgery detection approaches with additional ref... Read More about STIDNet: Identity-Aware Face Forgery Detection with Spatiotemporal Knowledge Distillation.

Novel Category Discovery without Forgetting for Automatic Target Recognition (2024)
Journal Article
Huang, H., Gao, F., Sun, J., Wang, J., Hussain, A., & Zhou, H. (2024). Novel Category Discovery without Forgetting for Automatic Target Recognition. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 4408-4420. https://d

We explore a cutting-edge concept known as C lass Incremental Learning in N ovel Category Discovery for Synthetic Aperture Radar T argets (CNT). This innovative task involves the challenge of identifying categories within unlabeled datasets by utiliz... Read More about Novel Category Discovery without Forgetting for Automatic Target Recognition.

Deep learning methods for early detection of Alzheimer’s disease using structural MR images: A survey (2024)
Journal Article
Hassen, S. B., Neji, M., Hussain, Z., Hussain, A., Alimi, A. M., & Frikha, M. (2024). Deep learning methods for early detection of Alzheimer’s disease using structural MR images: A survey. Neurocomputing, 576, Article 127325. https://doi.org/10.1016/j.n

In this paper, we present an extensive review of the most recent works for Alzheimer’s disease (AD) prediction, particularly Moderate Cognitive Impairment (MCI) conversion prediction. We aimed to identify the most useful brain-magnetic resonance imag... Read More about Deep learning methods for early detection of Alzheimer’s disease using structural MR images: A survey.

SAR Target Incremental Recognition Based on Features With Strong Separability (2024)
Journal Article
Gao, F., Kong, L., Lang, R., Sun, J., Wang, J., Hussain, A., & Zhou, H. (2024). SAR Target Incremental Recognition Based on Features With Strong Separability. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-13. https://doi.org/10.1109/tgrs.2024.

With the rapid development of deep learning technology, many synthetic aperture radar (SAR) target recognition algorithms based on convolutional neural networks have achieved exceptional performance on various datasets. However, conventional neural n... Read More about SAR Target Incremental Recognition Based on Features With Strong Separability.

A novel end-to-end deep convolutional neural network based skin lesion classification framework (2023)
Journal Article
A., R. S., Chamola, V., Hussain, A., Hussain, Z., & Albalwy, F. (2024). A novel end-to-end deep convolutional neural network based skin lesion classification framework. Expert Systems with Applications, 246, Article 123056. https://doi.org/10.1016/j.eswa.

Background: Skin diseases are reported to contribute 1.79% of the global burden of disease. The accurate diagnosis of specific skin diseases is known to be a challenging task due, in part, to variations in skin tone, texture, body hair, etc. Classif... Read More about A novel end-to-end deep convolutional neural network based skin lesion classification framework.

Advancing sepsis clinical research: harnessing transcriptomics for an omics-based strategy - a comprehensive scoping review (2023)
Journal Article
Rashid, A., Al-Obeidat, F., Kanthimathinathan, H. K., Benakatti, G., Hafez, W., Ramaiah, R., …Hussain, A. (2024). Advancing sepsis clinical research: harnessing transcriptomics for an omics-based strategy - a comprehensive scoping review. Informatics in

Sepsis continues to be recognized as a significant global health challenge across all ages and is characterized by a complex pathophysiology. In this scoping review, PRISMA-ScR guidelines were adhered to, and a transcriptomic methodology was adopted,... Read More about Advancing sepsis clinical research: harnessing transcriptomics for an omics-based strategy - a comprehensive scoping review.

Bare‐Bones particle Swarm optimization‐based quantization for fast and energy efficient convolutional neural networks (2023)
Journal Article
Tmamna, J., Ayed, E. B., Fourati, R., Hussain, A., & Ayed, M. B. (2024). Bare‐Bones particle Swarm optimization‐based quantization for fast and energy efficient convolutional neural networks. Expert Systems, 41(4), Article e13522. https://doi.org/10.1

Neural network quantization is a critical method for reducing memory usage and computational complexity in deep learning models, making them more suitable for deployment on resource-constrained devices. In this article, we propose a method called BBP... Read More about Bare‐Bones particle Swarm optimization‐based quantization for fast and energy efficient convolutional neural networks.

Machine Un-learning: An Overview of Techniques, Applications, and Future Directions (2023)
Journal Article
Sai, S., Mittal, U., Chamola, V., Huang, K., Spinelli, I., Scardapane, S., …Hussain, A. (2024). Machine Un-learning: An Overview of Techniques, Applications, and Future Directions. Cognitive Computation, 16, 482-506. https://doi.org/10.1007/s12559-023-1

ML applications proliferate across various sectors. Large internet firms employ ML to train intelligent models using vast datasets, including sensitive user information. However, new regulations like GDPR require data removal by businesses. Deleting... Read More about Machine Un-learning: An Overview of Techniques, Applications, and Future Directions.

Artificial intelligence-driven approach to identify and recommend the winner in a tied event in sports surveillance (2023)
Journal Article
Anwar, K., Zafar, A., Iqbal, A., Sohail, S. S., Hussain, A., Karaca, Y., …Muhammad, K. (2023). Artificial intelligence-driven approach to identify and recommend the winner in a tied event in sports surveillance. Fractals, 31(10), Article 2340149. https:

The proliferation of fractal artificial intelligence (AI)-based decision-making has propelled advances in intelligent computing techniques. Fractal AI-driven decision-making approaches are used to solve a variety of real-world complex problems, espec... Read More about Artificial intelligence-driven approach to identify and recommend the winner in a tied event in sports surveillance.