RESEARCHER PROFILE
Mohammed A. M. Abdullah
M
Ninevah University
Mohammed A. M. Abdullah works in Biometric Identification and Security, Advanced Steganography and Watermarking Techniques, Advanced Neural Network Applications, Medical Image Segmentation Techniques, Speech and Audio Processing. Recorded institutional associations include Ninevah University.
48Publications
733Citations
16H-index
Inclusion identifies researchers whose recorded research contributions may inform their university’s understanding of its research community. It does not rank individual research quality or establish current employment.
Selected research works
Up to 100 highly cited works; DOI links open the original research. Counts reflect the collected record, not real-time citation totals.
Robust Iris Segmentation Method Based on a New Active Contour Force With a Noncircular Normalization
2016 · 89 citationsOptimal Downlink Transmission for Cell-Free SWIPT Massive MIMO Systems With Active Eavesdropping
2019 · 73 citationsMulti-gradient features and elongated quinary pattern encoding for image-based facial expression recognition
2017 · 48 citationsGoing deeper: magnification‐invariant approach for breast cancer classification using histopathological images
2021 · 47 citationsFinger texture biometric verification exploiting Multi-scale Sobel Angles Local Binary Pattern features and score-based fusion
2017 · 39 citationsEfficient Machine Learning-Enhanced Channel Estimation for OFDM Systems
2021 · 33 citationsEnhanced Secrecy Performance of Multihop IoT Networks With Cooperative Hybrid-Duplex Jamming
2020 · 32 citationsA Framework for Iris Biometrics Protection: A Marriage Between Watermarking and Visual Cryptography
2016 · 32 citationsOptimal Fusion of Multispectral Optical and SAR Images for Flood Inundation Mapping through Explainable Deep Learning
2023 · 31 citationsRockDNet: Deep Learning Approach for Lithology Classification
2024 · 22 citationsA novel framework for cross-spectral iris matching
2016 · 21 citationsCombined i-Vector and Extreme Learning Machine Approach for Robust Speaker Identification and Evaluation with SITW 2016, NIST 2008, TIMIT Databases
2021 · 20 citationsAutomatic Brain Tumour Segmentation using fully Convolution Network and Transfer Learning
2019 · 20 citationsLBTS‐Net: A fast and accurate CNN model for brain tumour segmentation
2021 · 19 citationsThorough evaluation of TIMIT database speaker identification performance under noise with and without the G.712 type handset
2019 · 19 citationsSpatio-temporal modelling with multi-gradient features and elongated quinary pattern descriptor for dynamic facial expression recognition
2023 · 16 citationsComparisons of extreme learning machine and backpropagation-based i-vector approach for speaker identification
2019 · 16 citationsIris biometrie: Is the near-infrared spectrum always the best?
2015 · 16 citationsFast and Accurate Pupil Isolation Based on Morphology and Active Contour
2014 · 16 citationsSmart card with iris recognition for high security access environment
2011 · 16 citationsEfficient Noisy Sound-Event Mixture Classification Using Adaptive-Sparse Complex-Valued Matrix Factorization and OvsO SVM
2020 · 14 citationsSecuring Iris Images with a Robust Watermarking Algorithm based on Discrete Cosine Transform
2015 · 14 citationsCross-Spectral Iris Matching for Surveillance Applications
2017 · 13 citationsFast and accurate method for complete iris segmentation with active contour and morphology
2014 · 13 citationsQuantifying the Impact of Watermarking on Deep Learning Accuracy in Medical Image Classification
2024 · 9 citations