All Outputs (44)

An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction (2021)
Conference Proceeding
Kanwal, S., Rashid, J., Kim, J., Nisar, M. W., Hussain, A., Batool, S., & Kanwal, R. (2021). An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction. In 2021 International Conference on Innovative Computing (ICIC) (745-750). https://doi.org/10.1109/icic53490.2021.9693040

One of the most challenging problems in the telecommunications industry is predicting customer churn (CCP). Decision-makers and business experts stressed that acquiring new clients is more expensive than maintaining current ones. From current churn d... Read More about An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction.

An Integrated Approach for Cancer Survival Prediction Using Data Mining Techniques (2021)
Journal Article
Kaur, I., Doja, M. N., Ahmad, T., Ahmad, M., Hussain, A., Nadeem, A., & Abd El-Latif, A. A. (2021). An Integrated Approach for Cancer Survival Prediction Using Data Mining Techniques. Computational Intelligence and Neuroscience, 2021, Article 6342226. https://doi.org/10.1155/2021/6342226

Ovarian cancer is the third most common gynecologic cancers worldwide. Advanced ovarian cancer patients bear a significant mortality rate. Survival estimation is essential for clinicians and patients to understand better and tolerate future outcomes.... Read More about An Integrated Approach for Cancer Survival Prediction Using Data Mining Techniques.

A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls (2021)
Journal Article
Varone, G., Boulila, W., Lo Giudice, M., Benjdira, B., Mammone, N., Ieracitano, C., …Aguglia, U. (2022). A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls. Sensors, 22(1), Article 129. https://doi.org/10.3390/s22010129

Until now, clinicians are not able to evaluate the Psychogenic Non-Epileptic Seizures (PNES) from the rest-electroencephalography (EEG) readout. No EEG marker can help differentiate PNES cases from healthy subjects. In this paper, we have investigate... Read More about A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls.

FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning (2021)
Journal Article
Spinelli, I., Scardapane, S., Hussain, A., & Uncini, A. (2022). FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning. IEEE Transactions on Artificial Intelligence, 3(3), 344-354. https://doi.org/10.1109/tai.2021.3133818

Graph representation learning has become a ubiquitous component in many scenarios, ranging from social network analysis to energy forecasting in smart grids. In several applications, ensuring the fairness of the node (or graph) representations with r... Read More about FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning.

Attributes Guided Feature Learning for Vehicle Re-Identification (2021)
Journal Article
Li, H., Lin, X., Zheng, A., Li, C., Luo, B., He, R., & Hussain, A. (2022). Attributes Guided Feature Learning for Vehicle Re-Identification. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(5), 1211-1221. https://doi.org/10.1109/tetci.2021.3127906

Vehicle Re-ID has recently attracted enthusiastic attention due to its potential applications in smart city and urban surveillance. However, it suffers from large intra-class variation caused by view variations and illumination changes, and inter-cla... Read More about Attributes Guided Feature Learning for Vehicle Re-Identification.

Extending persian sentiment lexicon with idiomatic expressions for sentiment analysis (2021)
Journal Article
Dashtipour, K., Gogate, M., Gelbukh, A., & Hussain, A. (2021). Extending persian sentiment lexicon with idiomatic expressions for sentiment analysis. Social Network Analysis and Mining, 12(1), Article 9. https://doi.org/10.1007/s13278-021-00840-1

Nowadays, it is important for buyers to know other customer opinions to make informed decisions on buying a product or service. In addition, companies and organizations can exploit customer opinions to improve their products and services. However, th... Read More about Extending persian sentiment lexicon with idiomatic expressions for sentiment analysis.

A Novel Fingerprinting Technique for Data Storing and Sharing through Clouds (2021)
Journal Article
Fatima, M., Nisar, M. W., Rashid, J., Kim, J., Kamran, M., & Hussain, A. (2021). A Novel Fingerprinting Technique for Data Storing and Sharing through Clouds. Sensors, 21(22), Article 7647. https://doi.org/10.3390/s21227647

With the emerging growth of digital data in information systems, technology faces the challenge of knowledge prevention, ownership rights protection, security, and privacy measurement of valuable and sensitive data. On-demand availability of various... Read More about A Novel Fingerprinting Technique for Data Storing and Sharing through Clouds.

A novel multimodal fusion network based on a joint-coding model for lane line segmentation (2021)
Journal Article
Zou, Z., Zhang, X., Liu, H., Li, Z., Hussain, A., & Li, J. (2022). A novel multimodal fusion network based on a joint-coding model for lane line segmentation. Information Fusion, 80, 167-178. https://doi.org/10.1016/j.inffus.2021.10.008

There has recently been growing interest in utilizing multimodal sensors to achieve robust lane line segmentation. In this paper, we introduce a novel multimodal fusion architecture from an information theory perspective, and demonstrate its practica... Read More about A novel multimodal fusion network based on a joint-coding model for lane line segmentation.

Multi-lingual character handwriting framework based on an integrated deep learning based sequence-to-sequence attention model (2021)
Journal Article
Rabhi, B., Elbaati, A., Boubaker, H., Hamdi, Y., Hussain, A., & Alimi, A. M. (2021). Multi-lingual character handwriting framework based on an integrated deep learning based sequence-to-sequence attention model. Memetic Computing, 13, Article 459-475. https://doi.org/10.1007/s12293-021-00345-6

Online signals are rich in dynamic features such as trajectory chronology, velocity, pressure and pen up/down movements. Their offline counterparts consist of a set of pixels. Thus, online handwriting recognition accuracy is generally better than off... Read More about Multi-lingual character handwriting framework based on an integrated deep learning based sequence-to-sequence attention model.

A novel few-shot learning method for synthetic aperture radar image recognition (2021)
Journal Article
Yue, Z., Gao, F., Xiong, Q., Sun, J., Hussain, A., & Zhou, H. (2021). A novel few-shot learning method for synthetic aperture radar image recognition. Neurocomputing, 465, 215-227. https://doi.org/10.1016/j.neucom.2021.09.009

Synthetic aperture radar (SAR) image recognition is an important stage of SAR image interpretation. The standard convolutional neural network (CNN) has been successfully applied in the SAR image recognition due to its powerful feature extraction capa... Read More about A novel few-shot learning method for synthetic aperture radar image recognition.

Lane-DeepLab: Lane semantic segmentation in automatic driving scenarios for high-definition maps (2021)
Journal Article
Li, J., Jiang, F., Yang, J., Kong, B., Gogate, M., Dashtipour, K., & Hussain, A. (2021). Lane-DeepLab: Lane semantic segmentation in automatic driving scenarios for high-definition maps. Neurocomputing, 465, 15-25. https://doi.org/10.1016/j.neucom.2021.08.105

Accurate high-definition maps with lane markings are often used as the navigation back-end for commercial autonomous vehicles. Currently, most high-definition maps are manually constructed by human labelling. Therefore, it is urgently required to pro... Read More about Lane-DeepLab: Lane semantic segmentation in automatic driving scenarios for high-definition maps.

Effectiveness of virtual and augmented reality for improving knowledge and skills in medical students: protocol for a systematic review (2021)
Journal Article
Hussain, Z., Ng, D. M., Alnafisee, N., Sheikh, Z., Ng, N., Khan, A., …Sheikh, A. (2021). Effectiveness of virtual and augmented reality for improving knowledge and skills in medical students: protocol for a systematic review. BMJ Open, 11(8), Article e047004. https://doi.org/10.1136/bmjopen-2020-047004

Introduction Virtual reality (VR) and augmented reality (AR) technologies are increasingly being used in undergraduate medical education. We aim to evaluate the effectiveness of VR and AR technologies for improving knowledge and skills in medical stu... Read More about Effectiveness of virtual and augmented reality for improving knowledge and skills in medical students: protocol for a systematic review.

Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection (2021)
Journal Article
Cui, C., Lu, L., Tan, Z., & Hussain, A. (2021). Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection. Neurocomputing, 464, 252-264. https://doi.org/10.1016/j.neucom.2021.08.026

Segmentation-based methods are widely used for scene text detection due to their superiority in describing arbitrary-shaped text instances. However, two major problems still exist: (1) current label generation techniques are mostly empirical and lack... Read More about Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection.

A Hybrid-Domain Deep Learni/ng-Based BCI For Discriminating Hand Motion Planning From EEG Sources (2021)
Journal Article
Ieracitano, C., Morabito, F. C., Hussain, A., & Mammone, N. (2021). A Hybrid-Domain Deep Learni/ng-Based BCI For Discriminating Hand Motion Planning From EEG Sources. International Journal of Neural Systems, 31(9), Article 2150038. https://doi.org/10.1142/s0129065721500386

In this paper, a hybrid-domain deep learning (DL)-based neural system is proposed to decode hand movement preparation phases from electroencephalographic (EEG) recordings. The system exploits information extracted from the temporal-domain and time-fr... Read More about A Hybrid-Domain Deep Learni/ng-Based BCI For Discriminating Hand Motion Planning From EEG Sources.

Detection of Diabetic Eye Disease from Retinal Images Using a Deep Learning Based CenterNet Model (2021)
Journal Article
Nazir, T., Nawaz, M., Rashid, J., Mahum, R., Masood, M., Mehmood, A., …Hussain, A. (2021). Detection of Diabetic Eye Disease from Retinal Images Using a Deep Learning Based CenterNet Model. Sensors, 21(16), Article 5283. https://doi.org/10.3390/s21165283

Diabetic retinopathy (DR) is an eye disease that alters the blood vessels of a person suffering from diabetes. Diabetic macular edema (DME) occurs when DR affects the macula, which causes fluid accumulation in the macula. Efficient screening systems... Read More about Detection of Diabetic Eye Disease from Retinal Images Using a Deep Learning Based CenterNet Model.

Leveraging label hierarchy using transfer and multi-task learning: A case study on patent classification (2021)
Journal Article
Aroyehun, S. T., Angel, J., Majumder, N., Gelbukh, A., & Hussain, A. (2021). Leveraging label hierarchy using transfer and multi-task learning: A case study on patent classification. Neurocomputing, 464, 421-431. https://doi.org/10.1016/j.neucom.2021.07.057

When labels are organized into a meaningful taxonomy, the parent-child relationship between labels at different levels can give the classifier additional information not deducible from the data alone, especially with limited training data. As a case... Read More about Leveraging label hierarchy using transfer and multi-task learning: A case study on patent classification.

Cloud based scalable object recognition from video streams using orientation fusion and convolutional neural networks (2021)
Journal Article
Usman Yaseen, M., Anjum, A., Fortino, G., Liotta, A., & Hussain, A. (2022). Cloud based scalable object recognition from video streams using orientation fusion and convolutional neural networks. Pattern Recognition, 121, Article 108207. https://doi.org/10.1016/j.patcog.2021.108207

Object recognition from live video streams comes with numerous challenges such as the variation in illumination conditions and poses. Convolutional neural networks (CNNs) have been widely used to perform intelligent visual object recognition. Yet, CN... Read More about Cloud based scalable object recognition from video streams using orientation fusion and convolutional neural networks.

A Novel Multi-Stage Residual Feature Fusion Network for Detection of COVID-19 in Chest X-Ray Images (2021)
Journal Article
Fang, Z., Ren, J., MacLellan, C., Li, H., Zhao, H., Hussain, A., & Fortino, G. (2022). A Novel Multi-Stage Residual Feature Fusion Network for Detection of COVID-19 in Chest X-Ray Images. IEEE Transactions on Molecular, Biological and Multi-Scale Communications, 8(1), 17-27. https://doi.org/10.1109/TMBMC.2021.3099367

To suppress the spread of COVID-19, accurate diagnosis at an early stage is crucial, chest screening with radiography imaging plays an important role in addition to the real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test. Due... Read More about A Novel Multi-Stage Residual Feature Fusion Network for Detection of COVID-19 in Chest X-Ray Images.

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., …Imran, M. A. (2021). Public Perception of the Fifth Generation of Cellular Networks (5G) on Social Media. Frontiers in Big Data, 4, Article 640868. https://doi.org/10.3389/fdata.2021.640868

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.