Research Publications

Google Scholar: https://scholar.google.com/citations?user=sRBr2NQAAAAJ&hl=en

ResearchGate: https://www.researchgate.net/profile/Anindya_Das_Antar

ORCID: https://orcid.org/0000-0001-9912-8757

  • Anindya Das Antar, Masud Ahmed, Mohammad Shadman Ishrak, and Md Atiqur Rahman Ahad, “A Comparative Approach to Classification of Locomotion and Transportation Modes Using Smartphone Sensor Data”, 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2018 International Symposium on Wearable Computers (UbiComp/ISWC), Singapore, 2018. (Achieved Award in the Sussex-Huawei Locomotion (SHL) Challenge ) view

  • Trung Ngo, Md Atiqur Rahman Ahad, Daigo Muramatsu, Yasushi Makihara, Yasushi Yagi, Sozo Inoue, Tahera Hossain, Anindya Das Antar, and Masud Ahmed, “OU-ISIR Wearable Sensor-based Gait Challenge: Age and Gender”, The 12th IAPR International Conference on Biometrics (ICB 2019), Crete, Greece, 2019. view

  • Md Atiqur Rahman Ahad, Anindya Das Antar , and Omar Shahid (2019). Vision-based Action Understanding for Assistive Healthcare: A Short Review. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (pp. 1-11). view

  • Anindya Das Antar, Masud Ahmed, and Md Atiqur Rahman Ahad . “Challenges in Sensor-based Human Activity Recognition and a Comparative Analysis of Benchmark Datasets: A Review”. International Conference on Activity and Behavior Computing, USA In conjunction with ICIEV&IVPR, 2019. view

  • Masud Ahmed, Anindya Das Antar, and Md Atiqur Rahman Ahad . ” An Approach to Classify Human Activities in Real-time from Smartphone Sensor Data”. International Conference on Activity and Behavior Computing, USA In conjunction with ICIEV&IVPR, 2019.

  • Masud Ahmed , Anindya Das Antar, Tahera Hossain, Sozo Inoue, and Md Atiqur Rahman Ahad, “POIDEN: Position and Orientation Independent Deep Ensemble Network for the Classification of Locomotion and Transportation Modes”, 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2019 International Symposium on Wearable Computers (UbiComp/ISWC), London, United Kingdom, 2019.

Journals

  • Md Atiqur Rahman Ahad, Thanh Trung Ngo, Anindya Das Antar, Masud Ahmed, Tahera Hossain, Daigo Muramatsu, Yasushi Makihara, Sozo Inoue, and Yasushi Yagi, “Wearable Sensor-Based Gait Analysis for Age and Gender Estimation”. Sensors 2020, 20, 2424.
  • Md Atiqur Rahman Ahad, Masud Ahmed, Anindya Das Antar, Yasushi Makihara, Yasushi Yagi, “Action recognition using Kinematics Posture Feature on 3D skeleton joint locations”. Pattern Recognition Letters, 2021.
  • Masud Ahmed*, Anindya Das Antar*(Equal Contribution), Md Atiqur Rahman Ahad, “Static Postural Transition-based Technique and Efficient Feature Extraction for Sensor-based Activity Recognition”. Pattern Recognition Letters, 2021.
  • Anindya Das Antar, Masud Ahmed, and Md Atiqur Rahman Ahad, “Recognition of human locomotion on various transportations fusing smartphone sensors”. Pattern Recognition Letters, 2021.

Books

  • Md Atiqur Rahman Ahad, Anindya Das Antar, Masud Ahmed, “IoT Sensor-Based Activity Recognition – Human Activity Recognition”, Publisher: Springer Nature Switzerland AG, ISBN 978-3-030-51379-5, 2020.
    • Chapter 1: Introduction on Sensor-Based Human Activity Analysis: Background
    • Chapter 2: Basic Structure for Human Activity Recognition Systems: Preprocessing and Segmentation
    • Chapter 3: Methodology of Activity Recognition: Features and Learning Methods
    • Chapter 4: Human Activity Recognition: Data Collection and Design Issues
    • Chapter 5: Devices and Application Tools for Activity Recognition: Sensor Deployment and Primary Concerns
    • Chapter 6: Sensor-Based Benchmark Datasets: Comparison and Analysis
    • Chapter 7: An Overview of Classification Issues in Sensor-Based Activity Recognition
    • Chapter 8: Performance Evaluation in Activity Classification: Factors to Consider
    • Chapter 9: Deep Learning for Sensor-Based Activity Recognition: Recent Trends
    • Chapter 10: Sensor-Based Human Activity Recognition: Challenges Ahead

    • Book Chapters

    Thesis

    B.Sc. Thesis: Anindya Das Antar, Masud Ahmed, and MAR Ahad, “Sensor-based Activity Recognition Using Ensemble of Classifiers”, University of Dhaka, 2018.
    Link: https://drive.google.com/file/d/1ZOfgzYO8WlHqmUB6yGqg0aWg7fzv86ct/view?usp=sharing
    Supervisor: Prof. Md Atiqur Rahman Ahad, University of Dhaka; Osaka University ISIR
    http://aa.binbd.com/

    %d bloggers like this: