Modeling and Control of a Two-link Flexible Manipulator using Fuzzy Logic and Genetic Optimization Techniques. - Tahmina Zebin; M. S. Alam (J. Comput., 2012)

Inertial Sensor Based Modelling of Human Activity Classes: Feature Extraction and Multi-sensor Data Fusion Using Machine Learning Algorithms. - Tahmina Zebin; Patricia J. Scully; Krikor B. Ozanyan (eHealth 360°, 2016)

Human activity recognition with inertial sensors using a deep learning approach. - Tahmina Zebin; Patricia J. Scully; Krikor B. Ozanyan (IEEE SENSORS, 2016)

Evaluation of supervised classification algorithms for human activity recognition with inertial sensors. - Tahmina Zebin; Patricia J. Scully; Krikor B. Ozanyan (IEEE SENSORS, 2017)

Human activity recognition from inertial sensor time-series using batch normalized deep LSTM recurrent networks. - Tahmina Zebin; Matthew Sperrin; Niels Peek; Alexander J. Casson (EMBC, 2018)

Intrusion Detection and Classification with Autoencoded Deep Neural Network. - Shahadate Rezvy; Miltos Petridis; Aboubaker Lasebae; Tahmina Zebin (SecITC, 2018)

Implementation of a batch normalized deep LSTM recurrent network on a smartphone for human activity recognition. - Tahmina Zebin; Ertan Balaban; Krikor B. Ozanyan; Alexander J. Casson; Niels Peek (BHI, 2019)

Design and implementation of a deep recurrent model for prediction of readmission in urgent care using electronic health records. - Tahmina Zebin; Thierry J. Chaussalet (CIBCB, 2019)

A deep learning approach for length of stay prediction in clinical settings from medical records. - Tahmina Zebin; Shahadate Rezvy; Thierry J. Chaussalet (CIBCB, 2019)

An efficient deep learning model for intrusion classification and prediction in 5G and IoT networks. - Shahadate Rezvy; Yuan Luo; Miltos Petridis; Aboubaker Lasebae; Tahmina Zebin (CISS, 2019)

Physical activity based classification of serious mental illness group participants in the UK Biobank using ensemble dense neural networks. - Tahmina Zebin; Niels Peek; Alexander J. Casson (EMBC, 2019)

Design and Implementation of a Convolutional Neural Network on an Edge Computing Smartphone for Human Activity Recognition. - Tahmina Zebin; Patricia J. Scully; Niels Peek; Alexander J. Casson; Krikor B. Ozanyan (IEEE Access, 2019)

Transfer Learning For Endoscopy Disease Detection & Segmentation With Mask-RCNN Benchmark Architecture. - Shahadate Rezvy; Tahmina Zebin; Barbara Braden; Wei Pang 001; Stephen Taylor; Xiaohong W. Gao (EndoCV@ISBI, 2020)

COVID-19 detection and disease progression visualization: Deep learning on chest X-rays for classification and coarse localization. - Tahmina Zebin; Shahadate Rezvy (Appl. Intell., 2021)

An Explainable AI-Based Intrusion Detection System for DNS Over HTTPS (DoH) Attacks. - Tahmina Zebin; Shahadate Rezvy; Yuan Luo (IEEE Trans. Inf. Forensics Secur., 2022)

An Agricultural Precision Sprayer Deposit Identification System. - Harry Rogers; Beatriz de la Iglesia; Tahmina Zebin; Grzegorz Cielniak; Ben Magri (CASE, 2023)

Evaluating the Use of Interpretable Quantized Convolutional Neural Networks for Resource-Constrained Deployment. - Harry Rogers; Beatriz de la Iglesia; Tahmina Zebin (KDIR, 2023)

An Automated Precision Spraying Evaluation System. - Harry Rogers; Beatriz de la Iglesia; Tahmina Zebin; Grzegorz Cielniak; Ben Magri (TAROS, 2023)

Deep Learning for Precision Agriculture: Post-Spraying Evaluation and Deposition Estimation. - Harry Rogers; Tahmina Zebin; Grzegorz Cielniak; Beatriz de la Iglesia; Ben Magri (CoRR, 2024)

Advancing precision agriculture: domain-specific augmentations and robustness testing for convolutional neural networks in precision spraying evaluation. - Harry Rogers; Beatriz de la Iglesia; Tahmina Zebin; Grzegorz Cielniak; Ben Magri (Neural Comput. Appl., 2024)