Gastrointestinal diseases segmentation and classification based on duo-deep architectures. - Mehshan Ahmed Khan; Muhammad Attique Khan; Fawad Ahmed; Mamta Mittal; Lalit Mohan Goyal; D. Jude Hemanth; Suresh Chandra Satapathy (Pattern Recognit. Lett., 2020)

A novel CNN-LSTM-based approach to predict urban expansion. - Wadii Boulila; Hamza Ghandorh; Mehshan Ahmed Khan; Fawad Ahmed; Jawad Ahmad 001 (Ecol. Informatics, 2021)

Measuring Cognitive Load: Leveraging fNIRS and Machine Learning for Classification of Workload Levels. - Mehshan Ahmed Khan; Houshyar Asadi; Thuong N. Hoang; Chee Peng Lim; Saeid Nahavandi (ICONIP (9), 2023)

Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis. - Mehshan Ahmed Khan; Houshyar Asadi; Mohammad Reza Chalak Qazani; Adetokunbo Arogbonlo; Siamak Pedrammehr; Adnan Anwar; Asim Bhatti; Saeid Nahavandi; Chee Peng Lim (CoRR, 2024)

Functional near-infrared spectroscopy (fNIRS) and Eye tracking for Cognitive Load classification in a Driving Simulator Using Deep Learning. - Mehshan Ahmed Khan; Houshyar Asadi; Mohammad Reza Chalak Qazani; Chee Peng Lim; Saied Nahavandi (CoRR, 2024)

Predicting cognitive load in immersive driving scenarios with a hybrid CNN-RNN model. - Mehshan Ahmed Khan; Houshyar Asadi; Mohammad Reza Chalak Qazani; Adetokunbo Arogbonlo; Saeid Nahavandi; Chee Peng Lim (CoRR, 2024)

Application of artificial intelligence in cognitive load analysis using functional near-infrared spectroscopy: A systematic review. - Mehshan Ahmed Khan; Houshyar Asadi; Li Zhang 013; Mohammad Reza Chalak Qazani; Sam Oladazimi; Chu Kiong Loo; Chee Peng Lim; Saeid Nahavandi (Expert Syst. Appl., 2024)

Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis. - Mehshan Ahmed Khan; Houshyar Asadi; Mohammad Reza Chalak Qazani; Adetokunbo Arogbonlo; Siamak Pedrammehr; Adnan Anwar; Hailing Zhou; Lei Wei 002; Asim Bhatti; Sam Oladazimi; Burhan Khan; Saeid Nahavandi (Comput., 2025)