Muhammad E. H. Chowdhury - researchr alias

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Viewing Publication 1 - 23 from 23

2024

FPGA Implementation of Complex-Valued Neural Network for Polar-Represented Image ClassificationMaruf Ahmad, Lei Zhang 0092, Muhammad E. H. Chowdhury. sensors, 24(3):897, February 2024. [doi]

A novel deep learning technique for morphology preserved fetal ECG extraction from mother ECG using 1D-CycleGANPromit Basak, A. H. M. Nazmus Sakib, Muhammad E. H. Chowdhury, Nasser Al-Emadi, Huseyin Cagatay Yalcin, Shona Pedersen, Sakib Mahmud, Serkan Kiranyaz, Somaya Al-Máadeed. eswa, 235:121196, January 2024. [doi]

Robust and novel attention guided MultiResUnet model for 3D ground reaction force and moment prediction from foot kinematicsMd. Ahasan Atick Faisal, Sakib Mahmud, Muhammad E. H. Chowdhury, Amith Khandakar, Mosabber Uddin Ahmed, Abdulrahman Alqahtani, Mohammed Alhatou. nca, 36(3):1105-1121, January 2024. [doi]

A Reliable and Robust Deep Learning Model for Effective Recyclable Waste ClassificationMd. Mosarrof Hossen, Molla E. Majid, Saad Bin Abul Kashem, Amith Khandakar, Mohammad Nashbat, Azad Ashraf, Mazhar Hasan-Zia, Ali K. Ansaruddin Kunju, Saidul Kabir, Muhammad E. H. Chowdhury. access, 12:13809-13821, 2024. [doi]

The utility of a deep learning-based approach in Her-2/neu assessment in breast cancerSaidul Kabir, Semir Vranic, Rafif Mahmood Al Saady, Muhammad Salman Khan, Rusab Sarmun, Abdulrahman Alqahtani, Tariq O. Abbas, Muhammad E. H. Chowdhury. eswa, 238(Part C):122051, March 2024. [doi]

Surround-Screen Mobile Based Projection: Design and Implementation of Mobile Cave Virtual RealityAbdel Ghani Karkar, Muhammad E. H. Chowdhury, Naveed Nawaz, Somaya Al-Máadeed. access, 12:45094-45101, 2024. [doi]

Enhancing Bearing Fault Diagnosis Using Transfer Learning and Random Forest Classification: A Comparative Study on Variable Working ConditionsDurjay Saha, Md. Emdadul Hoque, Muhammad E. H. Chowdhury. access, 12:5986-6000, 2024. [doi]

Enhance data availability and network consistency using artificial neural network for IoTMujahid Tabassum, Sundresan Perumal, Saad Bin Abdul Kashem, Ponnan Suresh, Chinmay Chakraborty, Muhammad E. H. Chowdhury, Amith Khandakar. mta, 83(1):3111-3131, January 2024. [doi]

M2ECG: Wearable Mechanocardiograms to Electrocardiogram Estimation Using Deep LearningMalisha Islam Tapotee, Purnata Saha, Sakib Mahmud, Abdulrahman Alqahtani, Muhammad E. H. Chowdhury. access, 12:12963-12975, 2024. [doi]

2023

PCovNet+: A CNN-VAE anomaly detection framework with LSTM embeddings for smartwatch-based COVID-19 detectionFarhan Fuad Abir, Muhammad E. H. Chowdhury, Malisha Islam Tapotee, Adam Mushtak, Amith Khandakar, Sakib Mahmud, Anwarul Hasan. eaai, 122:106130, 2023. [doi]

IRv2-Net: A Deep Learning Framework for Enhanced Polyp Segmentation Performance Integrating InceptionResNetV2 and UNet Architecture with Test Time Augmentation TechniquesMD. Faysal Ahamed, Md. Khalid Syfullah, Ovi Sarkar, Md. Tohidul Islam, Md. Nahiduzzaman, Md. Rabiul Islam 0001, Amith Khandakar, Mohamed Arselene Ayari, Muhammad E. H. Chowdhury. sensors, 23(18):7724, September 2023. [doi]

EOG-Based Reading Detection in the Wild Using Spectrograms and Nested Classification ApproachSriman Bidhan Baray, Mosabber Uddin Ahmed, Muhammad E. H. Chowdhury, Koichi Kise. access, 11:105619-105632, 2023. [doi]

A Novel Approach to Monitor Head Movement Inside an MR Scanner Using Voltages Induced in Coils by Time-Varying GradientsEnamul Haque Bhuiyan, Muhammad E. H. Chowdhury, Paul Glover. access, 11:107004-107018, 2023. [doi]

Robust Peak Detection for Holter ECGs by Self-Organized Operational Neural NetworksMoncef Gabbouj, Serkan Kiranyaz, Junaid Malik, Muhammad Uzair Zahid, Turker Ince, Muhammad E. H. Chowdhury, Amith Khandakar, Anas Tahir. tnn, 34(11):9363-9374, November 2023. [doi]

Deep Learning Framework for Liver Segmentation from T1-Weighted MRI ImagesMd Sakib Abrar Hossain, Sidra Gul, Muhammad E. H. Chowdhury, Muhammad Salman Khan 0001, Md. Shaheenur Islam Sumon, Enamul Haque Bhuiyan, Amith Khandakar, Muhammad Maqsud Hossain, Abdus Sadique, Israa Al-Hashimi, Mohamed Arselene Ayari, Sakib Mahmud, Abdulrahman Alqahtani. sensors, 23(21):8890, November 2023. [doi]

Plant Disease Classifier: Detection of Dual-Crop Diseases Using Lightweight 2D CNN ArchitectureHasibul Islam Peyal, Md. Nahiduzzaman, Md. Abu Hanif Pramanik, Md. Khalid Syfullah, Saleh Mohammed Shahriar, Abida Sultana, Mominul Ahsan, Julfikar Haider, Amith Khandakar, Muhammad E. H. Chowdhury. access, 11:110627-110643, 2023. [doi]

Signer-Independent Arabic Sign Language Recognition System Using Deep Learning ModelKanchon Kanti Podder, Maymouna Ezeddin, Muhammad E. H. Chowdhury, Md. Shaheenur Islam Sumon, Anas M. Tahir, Mohamed Arselene Ayari, Proma Dutta, Amith Khandakar, Zaid Bin Mahbub, Muhammad Abdul Kadir. sensors, 23(16):7156, August 2023. [doi]

Deep Learning Technique for Congenital Heart Disease Detection Using Stacking-Based CNN-LSTM Models From Fetal Echocardiogram: A Pilot StudyTawsifur Rahman, Mahmoud Khatib A. A. Al-Ruweidi, Md. Shaheenur Islam Sumon, Reema Youssef Kamal, Muhammad E. H. Chowdhury, Huseyin Cagatay Yalcin. access, 11:110375-110390, 2023. [doi]

Fetal ECG extraction from maternal ECG using deeply supervised LinkNet++ modelArafat Rahman, Sakib Mahmud, Muhammad E. H. Chowdhury, Huseyin Cagatay Yalcin, Amith Khandakar, Onur Mutlu, Zaid Bin Mahbub, Reema Youssef Kamal, Shona Pedersen. eaai, 123(Part C):106414, 2023. [doi]

2019

Reference Layer Artefact Subtraction (RLAS): Electromagnetic SimulationsMuhammad E. H. Chowdhury, Amith Khandakar, Karen J. Mullinger, Belayat Hossain, Nasser Al-Emadi, Andre Antunes, Richard Bowtell. access, 7:17882-17895, 2019. [doi]

2018

Exploring the origins of EEG motion artefacts during simultaneous fMRI acquisition: Implications for motion artefact correctionGlyn S. Spencer, James A. Smith, Muhammad E. H. Chowdhury, Richard Bowtell, Karen J. Mullinger. neuroimage, 173:188-198, 2018. [doi]

2014

Reference layer artefact subtraction (RLAS): A novel method of minimizing EEG artefacts during simultaneous fMRIMuhammad E. H. Chowdhury, Karen J. Mullinger, Paul Glover, Richard Bowtell. neuroimage, 84:307-319, 2014. [doi]

Corrigendum to "Reference layer artefact subtraction (RLAS): A novel method of minimizing EEG artefacts during simultaneous fMRI" [Neuroimage 84 (2014) 307-319]Muhammad E. H. Chowdhury, Karen J. Mullinger, Paul Glover, Richard Bowtell. neuroimage, 98:547, 2014. [doi]

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