Skip to main content

Research Repository

Advanced Search

All Outputs (33)

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.

Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances (2020)
Presentation / Conference Contribution
Ahmed, R., Dashtipour, K., Gogate, M., Raza, A., Zhang, R., Huang, K., Hawalah, A., Adeel, A., & Hussain, A. (2019, July). Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances. Presented at 10th International Conference, BICS 2019, Guangzhou, China

In pattern recognition, automatic handwriting recognition (AHWR) is an area of research that has developed rapidly in the last few years. It can play a significant role in broad-spectrum of applications rending from, bank cheque processing, applicati... Read More about Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances.

Random Features and Random Neurons for Brain-Inspired Big Data Analytics (2020)
Presentation / Conference Contribution
Gogate, M., Hussain, A., & Huang, K. (2019, November). Random Features and Random Neurons for Brain-Inspired Big Data Analytics. Presented at 2019 International Conference on Data Mining Workshops (ICDMW), Beijing, China

With the explosion of Big Data, fast and frugal reasoning algorithms are increasingly needed to keep up with the size and the pace of user-generated contents on the Web. In many real-time applications, it is preferable to be able to process more data... Read More about Random Features and Random Neurons for Brain-Inspired Big Data Analytics.

Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection (2018)
Presentation / Conference Contribution
Ieracitano, C., Adeel, A., Gogate, M., Dashtipour, K., Morabito, F., Larijani, H., …Hussain, A. (2018). Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection. . https://doi.org/10.1007/978-3-030-00563-4_74

Attackers have developed ever more sophisticated and intelligent ways to hack information and communication technology (ICT) systems. The extent of damage an individual hacker can carry out upon infiltrating a system is well understood. A potentially... Read More about Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection.

Exploiting Deep Learning for Persian Sentiment Analysis (2018)
Presentation / Conference Contribution
Dashtipour, K., Gogate, M., Adeel, A., Ieracitano, C., Larijani, H., & Hussain, A. (2018, July). Exploiting Deep Learning for Persian Sentiment Analysis. Presented at 9th International Conference, BICS 2018, Xi'an, China

The rise of social media is enabling people to freely express their opinions about products and services. The aim of sentiment analysis is to automatically determine subject’s sentiment (e.g., positive, negative, or neutral) towards a particular aspe... Read More about Exploiting Deep Learning for Persian Sentiment Analysis.

A comparative study of Persian sentiment analysis based on different feature combinations (2018)
Presentation / Conference Contribution
Dashtipour, K., Gogate, M., Adeel, A., Hussain, A., Alqarafi, A., & Durrani, T. (2017, July). A comparative study of Persian sentiment analysis based on different feature combinations. Presented at International Conference in Communications, Signal Processing, and Systems, Harbin, China

In recent years, the use of internet and correspondingly the number of online reviews, comments and opinions have increased significantly. It is indeed very difficult for humans to read these opinions and classify them accurately. Consequently, there... Read More about A comparative study of Persian sentiment analysis based on different feature combinations.

Toward's Arabic multi-modal sentiment analysis (2018)
Presentation / Conference Contribution
Alqarafi, A., Adeel, A., Gogate, M., Dashitpour, K., Hussain, A., & Durrani, T. (2019). Toward's Arabic multi-modal sentiment analysis. . https://doi.org/10.1007/978-981-10-6571-2_290

In everyday life, people use internet to express and share opinions, facts, and sentiments about products and services. In addition, social media applications such as Facebook, Twitter, WhatsApp, Snapchat etc., have become important information shari... Read More about Toward's Arabic multi-modal sentiment analysis.

A novel brain-inspired compression-based optimised multimodal fusion for emotion recognition (2018)
Presentation / Conference Contribution
Gogate, M., Adeel, A., & Hussain, A. (2018). A novel brain-inspired compression-based optimised multimodal fusion for emotion recognition. . https://doi.org/10.1109/SSCI.2017.8285377

The curse of dimensionality is a well-established phenomenon. However, the properties of high dimensional data are often poorly understood and overlooked during the process of data modelling and analysis. Similarly, how to optimally fuse different mo... Read More about A novel brain-inspired compression-based optimised multimodal fusion for emotion recognition.

Deep learning driven multimodal fusion for automated deception detection (2018)
Presentation / Conference Contribution
Gogate, M., Adeel, A., & Hussain, A. (2018). Deep learning driven multimodal fusion for automated deception detection. . https://doi.org/10.1109/SSCI.2017.8285382

Humans ability to detect lies is no more accurate than chance according to the American Psychological Association. The state-of-the-art deception detection methods, such as deception detection stem from early theories and polygraph have proven to be... Read More about Deep learning driven multimodal fusion for automated deception detection.

Towards Next-Generation Lip-Reading Driven Hearing-Aids: A preliminary Prototype Demo (2017)
Presentation / Conference Contribution
Adeel, A., Gogate, M., & Hussain, A. (2017, August). Towards Next-Generation Lip-Reading Driven Hearing-Aids: A preliminary Prototype Demo. Presented at 1st International Workshop on Challenges in Hearing Assistive Technology (CHAT 2017), Stockholm, Sweden

Speech enhancement aims to enhance the perceived speech quality and intelligibility in the presence of noise. Classical speech enhancement methods are mainly based on audio only processing which often perform poorly in adverse conditions, where overw... Read More about Towards Next-Generation Lip-Reading Driven Hearing-Aids: A preliminary Prototype Demo.

Persian Named Entity Recognition (2017)
Presentation / Conference Contribution
Dashtipour, K., Gogate, M., Adeel, A., Algarafi, A., Howard, N., & Hussain, A. (2017). Persian Named Entity Recognition. . https://doi.org/10.1109/ICCI-CC.2017.8109733

Named Entity Recognition (NER) is an important natural language processing (NLP) tool for information extraction and retrieval from unstructured texts such as newspapers, blogs and emails. NER involves processing unstructured text for classification... Read More about Persian Named Entity Recognition.

Complex-valued computational model of hippocampal CA3 recurrent collaterals (2017)
Presentation / Conference Contribution
Shiva, A., Gogate, M., Howard, N., Graham, B., & Hussain, A. (2017). Complex-valued computational model of hippocampal CA3 recurrent collaterals. . https://doi.org/10.1109/ICCI-CC.2017.8109745

Complex planes are known to simplify the complexity of real world problems, providing a better comprehension of their functionality and design. The need for complex numbers in both artificial and biological neural networks is equally well established... Read More about Complex-valued computational model of hippocampal CA3 recurrent collaterals.