Prediction of Fire Signatures Based on Fractional Order Optical Flow and Convolution Neural Network. - Shreya Gupta; Muzammil Khan 002; Pushpendra Kumar (CVIP (2), 2022)

A Segmentation Based Robust Fractional Variational Model for Motion Estimation. - Pushpendra Kumar; Muzammil Khan 002; Nitish Kumar Mahala (CVIP (1), 2022)

Smoke Detection Using its Static and Dynamic Features Based on Fractional Order Optical Flow and Deep Learning Models for Fire Prediction. - Muzammil Khan 002; Nitish Kumar Mahala; Pushpendra Kumar (ICCCNT, 2023)

Study of Various Deep Learning Models for COVID-19 Detection Based on Fractional Order Optical Flow. - Bhavana Singh; Muzammil Khan 002; Pushpendra Kumar (ICCCNT, 2023)

A Relative Analysis of Different CNN Based Models for COVID-19 Detection using CXR and CT Images. - Pushpendra Kumar; Dipshi Jayaswal; Muzammil Khan 002; Bhavana Singh (ICMLDE, 2023)

Fire Detection Using Level Set Segmentation Based Fractional Order Optical Flow and 4D Fire Features with Mixed Data CNN-LSTM Model. - Muzammil Khan 002; Pushpendra Kumar (TENCON, 2023)

A Non-Local Weighted Fractional Order Variational Model for Smoke Detection Using Deep Learning Models. - Nitish Kumar Mahala; Muzammil Khan 002; Pushpendra Kumar (TENCON, 2023)

A level set based fractional order variational model for motion estimation in application oriented spectrum. - Muzammil Khan 002; Pushpendra Kumar (Expert Syst. Appl., 2023)

Reliable Smoke Detection via Optical Flow-Guided Feature Fusion and Transformer-Based Uncertainty Modeling. - Nitish Kumar Mahala; Muzammil Khan 002; Pushpendra Kumar (CoRR, 2025)