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Muzammil Khan
Muzammil Khan
Researcher at RaM Group, University of Twente, the Netherlands
Verified email at utwente.nl
Title
Cited by
Cited by
Year
A nonlinear modeling of fractional order based variational model in optical flow estimation
M Khan, P Kumar
Optik 261, 169136, 2022
172022
A level set based fractional order variational model for motion estimation in application oriented spectrum
M Khan, P Kumar
Expert Systems with Applications, 119628, 2023
112023
Development of an IR Video Surveillance System Based on Fractional Order TV-Model
P Kumar, M Khan, S Gupta
2021 International Conference on Control, Automation, Power and Signal …, 2021
62021
Caputo derivative based nonlinear fractional order variational model for motion estimation in various application oriented spectrum
M Khan, NK Mahala, P Kumar
Sādhanā 49 (1), 1-28, 2024
42024
Early Prediction of COVID-19 Suspects Based on Fractional Order Optical Flow
P Kumar, M Khan
2021 5th International Conference on Information Systems and Computer …, 2021
42021
Prediction of Fire Signatures Based on Fractional Order Optical Flow and Convolution Neural Network
S Gupta, M Khan, P Kumar
Computer Vision and Image Processing: 7th International Conference, CVIP …, 2023
32023
Charbonnier-Marchaud Based Fractional Variational Model for Motion Estimation in Multispectral Vision System
P Kumar, M Khan
Journal of Physics: Conference Series 2327 (1), 012031, 2022
32022
A Segmentation Based Robust Fractional Variational Model for Motion Estimation
P Kumar, M Khan, NK Mahala
Computer Vision and Image Processing: 7th International Conference, CVIP …, 2023
22023
A Vision Based Fractional Order TV-Model for Underwater Motion Estimation
M Khan, P Kumar
2021 IEEE Bombay Section Signature Conference (IBSSC), 1-6, 2021
22021
Study of Various Deep Learning Models for COVID-19 Detection Based on Fractional Order Optical Flow
B Singh, M Khan, P Kumar
2023 14th International Conference on Computing Communication and Networking …, 2023
12023
Identification of Potential Biomarkers for Diabetes Mellitus Using Gene Expression Datasets, Machine Learning, and R Packages to Predict the Risk of Diabetes
S Jena, P Kumar, D Mishra, M Khan
Artificial Intelligence in Healthcare, 47-76, 2024
2024
Early Detection of Diabetic Foot Ulcers Using Optical Flow–Based Ensemble Learning CNN Framework
B Singh, P Kumar, M Khan
Artificial Intelligence in Healthcare, 26-46, 2024
2024
A Nonlinear Fractional Order Optical Flow and CNN Based Framework for Fire Prediction Using Smoke Features
NK Mahala, M Khan, P Kumar
2024 OPJU International Technology Conference (OTCON) on Smart Computing for …, 2024
2024
A nonlinear fractional order variational model for the robust estimation of optical flow
A Kumar, B Singh, M Khan, P Kumar
2024 OPJU International Technology Conference (OTCON) on Smart Computing for …, 2024
2024
A Relative Analysis of Different CNN Based Models for COVID-19 Detection using CXR and CT Images
P Kumar, D Jayaswal, M Khan, B Singh
Procedia Computer Science 235, 3163-3173, 2024
2024
Ensemble learning and skip connection-based CNN framework for COVID-19 identification using CXR and CT images
PK Muzammil Khan, Bhavana Singh
International Journal of Computational Vision and Robotics, 2024
2024
CNN-Based Fire Prediction Using Fractional Order Optical Flow and Smoke Features
M Khan, P Kumar, NK Mahala
Applications of Optimization and Machine Learning in Image Processing and IoT, 2023
2023
A Non-Local Weighted Fractional Order Variational Model for Smoke Detection Using Deep Learning Models
NK Mahala, M Khan, P Kumar
TENCON 2023-2023 IEEE Region 10 Conference (TENCON), 146-151, 2023
2023
Fire Detection Using Level Set Segmentation Based Fractional Order Optical Flow and 4D Fire Features with Mixed Data CNN-LSTM Model
M Khan, P Kumar
TENCON 2023-2023 IEEE Region 10 Conference (TENCON), 152-157, 2023
2023
Smoke Detection Using its Static and Dynamic Features Based on Fractional Order Optical Flow and Deep Learning Models for Fire Prediction
M Khan, NK Mahala, P Kumar
2023 14th International Conference on Computing Communication and Networking …, 2023
2023
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