All Outputs (46)

Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform (2022)
Journal Article
Abd, M. H., Al-Suhail, G. A., Tahir, F. R., Ali Ali, A. M., Abbood, H. A., Dashtipour, K., …Ahmad, J. (2022). Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform. Remote Sensing, 14(9), Article 1984. https://doi.org/10.3390/

There is no doubt that chaotic systems are still attractive issues in various radar applications and communication systems. In this paper, we present a new 0.3 GHz mono-static microwave chaotic radar. It includes a chaotic system based on a time-dela... Read More about Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform.

Personalized wearable electrodermal sensing-based human skin hydration level detection for sports, health and wellbeing (2022)
Journal Article
Liaqat, S., Dashtipour, K., Rizwan, A., Usman, M., Shah, S. A., Arshad, K., …Ramzan, N. (2022). Personalized wearable electrodermal sensing-based human skin hydration level detection for sports, health and wellbeing. Scientific Reports, 12(1), Article 3

Personalized hydration level monitoring play vital role in sports, health, wellbeing and safety of a person while performing particular set of activities. Clinical staff must be mindful of numerous physiological symptoms that identify the optimum hyd... Read More about Personalized wearable electrodermal sensing-based human skin hydration level detection for sports, health and wellbeing.

Detecting Alzheimer’s Disease Using Machine Learning Methods (2022)
Presentation / Conference Contribution
Dashtipour, K., Taylor, W., Ansari, S., Zahid, A., Gogate, M., Ahmad, J., Assaleh, K., Arshad, K., Ali Imran, M., & Abbasi, Q. (2021, October). Detecting Alzheimer’s Disease Using Machine Learning Methods. Presented at 16th EAI International Conference,

As the world is experiencing population growth, the portion of the older people, aged 65 and above, is also growing at a faster rate. As a result, the dementia with Alzheimer’s disease is expected to increase rapidly in the next few years. Currently,... Read More about Detecting Alzheimer’s Disease Using Machine Learning Methods.

Comparing the Performance of Different Classifiers for Posture Detection (2022)
Presentation / Conference Contribution
Suresh Kumar, S., Dashtipour, K., Gogate, M., Ahmad, J., Assaleh, K., Arshad, K., Imran, M. A., Abbasi, Q., & Ahmad, W. (2021, October). Comparing the Performance of Different Classifiers for Posture Detection. Presented at 16th EAI International Conferen

Human Posture Classification (HPC) is used in many fields such as human computer interfacing, security surveillance, rehabilitation, remote monitoring, and so on. This paper compares the performance of different classifiers in the detection of 3 post... Read More about Comparing the Performance of Different Classifiers for Posture Detection.

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

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.

Extending persian sentiment lexicon with idiomatic expressions for sentiment analysis (2021)
Journal Article
Dashtipour, K., Gogate, M., Gelbukh, A., & Hussain, A. (2022). 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.

Intrusion Detection Framework for the Internet of Things Using a Dense Random Neural Network (2021)
Journal Article
Latif, S., Huma, Z. E., Jamal, S. S., Ahmed, F., Ahmad, J., Zahid, A., …Abbasi, Q. H. (2022). Intrusion Detection Framework for the Internet of Things Using a Dense Random Neural Network. IEEE Transactions on Industrial Informatics, 18(9), 6435-6444. ht

The Internet of Things (IoT) devices, networks, and applications have become an integral part of modern societies. Despite their social, economic, and industrial benefits, these devices and networks are frequently targeted by cybercriminals. Hence, I... Read More about Intrusion Detection Framework for the Internet of Things Using a Dense Random Neural Network.

Ultra-low-power, high-accuracy 434 MHz indoor positioning system for smart homes leveraging machine learning models (2021)
Journal Article
Nawaz, H., Tahir, A., Ahmed, N., Fayyaz, U. U., Mahmood, T., Jaleel, A., Gogate, M., Dashtipour, K., Masud, U., & Abbasi, Q. (2021). Ultra-low-power, high-accuracy 434 MHz indoor positioning system for smart homes leveraging machine learning models. Entro

Global navigation satellite systems have been used for reliable location-based services in outdoor environments. However, satellite-based systems are not suitable for indoor positioning due to low signal power inside buildings and low accuracy of 5 m... Read More about Ultra-low-power, high-accuracy 434 MHz indoor positioning system for smart homes leveraging machine learning models.

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

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.

A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration (2021)
Journal Article
Liaqat, S., Dashtipour, K., Zahid, A., Arshad, K., Ullah Jan, S., Assaleh, K., & Ramzan, N. (2021). A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration. Frontiers in Communications and Networks,

Atrial fibrillation (AF) is one of the most common types of cardiac arrhythmia, with a prevalence of 1–2% in the community, increasing the risk of stroke and myocardial infarction. Early detection of AF, typically causing an irregular and abnormally... Read More about A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration.

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.

Novel Ensemble Algorithm for Multiple Activity Recognition in Elderly People Exploiting Ubiquitous Sensing Devices (2021)
Journal Article
Liaqat, S., Dashtipour, K., Shah, S. A., Rizwan, A., Alotaibi, A. A., Althobaiti, T., …Ramzan, N. (2021). Novel Ensemble Algorithm for Multiple Activity Recognition in Elderly People Exploiting Ubiquitous Sensing Devices. IEEE Sensors Journal, 21(16), 1

Ambient assisted living is good way to look after ageing population that enables us to detect human’s activities of daily living (ADLs) and postures, as number of older adults are increasing at rapid pace. Posture detection is used to provide the ass... Read More about Novel Ensemble Algorithm for Multiple Activity Recognition in Elderly People Exploiting Ubiquitous Sensing Devices.

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.

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.

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 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.

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..