no code implementations • 7 Feb 2022 • Aamir Arsalan, Syed Muhammad Anwar, Muhammad Majid
This paper presents a comprehensive review of methods covering significant subjective and objective human stress detection techniques available in the literature.
no code implementations • 8 Jan 2021 • Ali Nawaz, Syed Muhammad Anwar, Rehan Liaqat, Javid Iqbal, Ulas Bagci, Muhammad Majid
Alzheimer's disease (AD) is a progressive and incurable neurodegenerative disease which destroys brain cells and causes loss to patient's memory.
no code implementations • 17 Jul 2019 • Sanay Muhammad Umar Saeed, Syed Muhammad Anwar, Humaira Khalid, Muhammad Majid, Ulas Bagci
Stress research is a rapidly emerging area in thefield of electroencephalography (EEG) based signal processing. The use of EEG as an objective measure for cost effective andpersonalized stress management becomes important in particularsituations such as the non-availability of mental health facilities. In this study, long-term stress is classified using baseline EEGsignal recordings.
no code implementations • 13 May 2019 • Aamir Arsalan, Muhammad Majid, Syed Muhammad Anwar, Ulas Bagci
In this paper, we present an experimental study for the classification of perceived human stress using non-invasive physiological signals.
no code implementations • 13 May 2019 • Aasim Raheel, Muhammad Majid, Syed Muhammad Anwar, Ulas Bagci
The response to this enhanced multimedia content (mulsemedia) is evaluated in terms of the appreciation/emotion by using human brain signals.
no code implementations • 4 Sep 2017 • Syed Muhammad Anwar, Muhammad Majid, Adnan Qayyum, Muhammad Awais, Majdi Alnowami, Muhammad Khurram Khan
Deep learning is successfully used as a tool for machine learning, where a neural network is capable of automatically learning features.
no code implementations • 1 Aug 2017 • Saddam Hussain, Syed Muhammad Anwar, Muhammad Majid
A patch based approach along with an inception module is used for training the deep network by extracting two co-centric patches of different sizes from the input images.
1 code implementation • 24 Mar 2017 • Adnan Qayyum, Syed Muhammad Anwar, Muhammad Awais, Muhammad Majid
The learned features and the classification results are used to retrieve medical images.