Dr Md Atiqur Rahman Ahad
Professor
Department of Engineering & Computing , School Of Architecture, Computing And Engineering
Md Atiqur Rahman Ahad is an Associate Professor of Artificial Intelligence and Machine Learning, and Champion, Research and Innovation in the Department of Computer Science and Digital Technologies.
Qualifications
- PhD
- Senior Member, IEEE
- Senior Member, OPTICA (formerly OSA)
- Member, ACM (Association for Computing Machinery)
- Member, IAPR (International Association for Pattern Recognition)
- Professor (former), University of Dhaka
- Specially Appointed Associate Professor (former), Osaka University
- Visiting Professor (former), Brawijaya University
Publications
The last four years of publications can be viewed below.
Full publications list
Visit the research repository to view a full list of publications
- Nurse Activity Recognition based on Temporal Frequency Features in: Ahad, M. A. R., Inoue, S., Lopez, G. and Hossain, T. (ed.) Human Activity and Behavior Analysis: Advances in Computer Vision and Sensors, Vol. 1. CRC Press: Taylor & Francis Group, pp.311-322
- A Sequential-based Analytical Approach for Nurse Care Activity Forecasting in: Ahad, M. A. R., Inoue, S., Lopez, G. and Hossain, T. (ed.) Human Activity and Behavior Analysis Advances in Computer Vision and Sensors: Volume 1. CRC Press: Taylor & Francis Group, pp.349-368
- Psychological Analysis in Human-Robot Collaboration from Workplace Stress Factors: A Review in: Ahad, M. A. R., Inoue, S., Lopez, G. and Hossain, T. (ed.) Human Activity and Behavior Analysis: Advances in Computer Vision and Sensors: Volume 2. Boca Raton, Florida: CRC Press: Taylor & Francis Group, pp.165-197
- Static Sign Language Recognition Using Segmented Images and HOG on Cluttered Backgrounds in: Ahad, M. A. R., Inoue, S., Lopez, G. and Hossain, T. (ed.) Human Activity and Behavior Analysis: Advances in Computer Vision and Sensors: Volume 2. Boca Raton, Florida: CRC Press: Taylor & Francis Group, pp.23-45
- Human Activity and Behavior Analysis: Advances in Computer Vision and Sensors: Volume 2 Boca Raton, Florida: CRC Press: Taylor & Francis Group
- Human Activity and Behavior Analysis Advances in Computer Vision and Sensors: Volume 1 Boca Raton, Florida: CRC Press: Taylor & Francis Group
- Computer Vision: Challenges, Trends and Opportunities New York, USA: CRC Press: Taylor & Francis Group
- E2ETCA: End-to-end training of CNN and attention ensembles for rice disease diagnosis Journal of Integrative Agriculture. In Press. https://doi.org/10.1016/j.jia.2024.03.075
- Elderly Motion Analysis to Estimate Emotion: A Systematic Review International Journal of Activity and Behavior Computing. (2), pp. 1-23. https://doi.org/10.60401/ijabc.23
- Integrating Human Behavioral Model for Intimate-distance Human Robot Collaboration International Journal of Activity and Behavior Computing. (2), pp. 1-26. https://doi.org/10.60401/ijabc.27
- Computer Vision and Image Analysis for Industry 4.0 NY: CRC Press: Taylor & Francis Group
- Annotator-dependent uncertainty-aware estimation of gait relative attributes Pattern Recognition. 136 (Art. 109197). https://doi.org/10.1016/j.patcog.2022.109197
- Advances in Human Action, Activity and Gesture Recognition Pattern Recognition Letters. 155, pp. 186-190. https://doi.org/10.1016/j.patrec.2021.11.003
- Automated detection approaches to autism spectrum disorder based on human activity analysis: A review Cognitive Computation. 14, pp. 1773-1800. https://doi.org/10.1007/s12559-021-09895-w
- A Sleep Monitoring System Using Ultrasonic Sensors International Journal of Biomedical Soft Computing and Human Sciences. 27 (1), pp. 13-20. https://doi.org/10.24466/ijbschs.27.1_13
- MUMAP: Modified Ultralightweight Mutual Authentication protocol for RFID enabled IoT networks Journal of the Institute of Industrial Applications Engineers. 9 (2), pp. 33-39. https://doi.org/10.12792/JIIAE.9.33
- Emotion Recognition from EEG Signal Focusing on Deep Learning and Shallow Learning Techniques IEEE Access. 9, pp. 94601-94624. https://doi.org/10.1109/ACCESS.2021.3091487
- Static Postural Transition-based Technique and Efficient Feature Extraction for Sensor-based Activity Recognition Pattern Recognition Letters. 147, pp. 25-33. https://doi.org/10.1016/j.patrec.2021.04.001
- Recognition of human locomotion on various transportations fusing smartphone sensors Pattern Recognition Letters. 148, pp. 146-153. https://doi.org/10.1016/j.patrec.2021.04.015
- Activity Recognition from Accelerometer Data Based on Supervised Learning for Wireless Sensor Network International Journal of Biomedical Soft Computing and Human Sciences. 26 (2), pp. 73-86. https://doi.org/10.24466/ijbschs.26.2_73
- Action recognition using Kinematics Posture Feature on 3D skeleton joint locations Pattern Recognition Letters. 145, pp. 216-224. https://doi.org/10.1016/j.patrec.2021.02.013
- Exploring Human Activities Using eSense Earable Device in: Ahad, M., Inoue, S., Roggen, D. and Fujinami, K. (ed.) Activity and Behavior Computing. Springer Singapore, pp.169–185
- Contactless Human Monitoring: Challenges and Future Direction in: Ahad, M., Mahbub, U. and Ahad, M. (ed.) Contactless Human Activity Analysis. Springer, Cham, pp.335-364
- Contactless Human Emotion Analysis Across Different Modalities in: Ahad, M., Mahbub, U. and Rahman, T. (ed.) Contactless Human Activity Analysis. Springer, Cham, pp.237-269
- Contactless Fall Detection for the Elderly in: Ahad, M., Mahbub, U. and Rahman, T. (ed.) Contactless Human Activity Analysis. Springer, Cham, pp.203-235