Research Activities

Publications

Journal

  • S. Tabassum, N. Abedin, M. M. Rahman, M. M. Rahman, M. T. Ahmed, R. I. Maruf, A. Ahmed, "An Online Cursive Handwritten Medical Words Recognition System for Busy Doctors in Developing Countries for Ensuring Efficient Healthcare Service Delivery", Scientific Reports (2022), 12(1), 1-13.

Impact factor: 4.996 (2021)

⇲ publication

  • S. Tabassum, M. S. Ullah, N. H. Al-nur, S. Shatabda, "Poribohon-BD: Bangladeshi Local Vehicle Image Dataset with Annotation for Classification", Data in brief 33 (2020), 106465.

Impact factor: 2.4 (2021)

⇲ publication ⇲ dataset


Conference Paper

  • S. Tabassum, N. Abedin, R. I. Maruf, M. T. Ahmed, A. Ahmed, "Improving Health Status Prediction by Applying Appropriate Missing Value Imputation Technique", The 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech 2022), Osaka, Japan, March 2022.

⇲ publication

  • S. Tabassum, R. Takahashi, M. M. Rahman, I. Yosuke, L. Sixian, M. M. Rahman, A. Ahmed, "Recognition of Doctors' Cursive Handwritten Medical Words by using Bidirectional LSTM and SRP Data Augmentation", 2021 IEEE Technology & Engineering Management Conference – Europe (TEMSCON-EUR), Dubrovnik, Europe, May 2021.

⇲ publication ⇲ certificate

  • K. K. Podder, S. Tabassum, L. E. Khan, K. M. A. Salam, R. I. Maruf, A. Ahmed, "Design of a Sign Language Transformer to Enable the Participation of Persons with Disabilities in Remote Healthcare Systems for Ensuring Universal Healthcare Coverage", 2021 IEEE Technology & Engineering Management Conference – Europe (TEMSCON-EUR), Dubrovnik, Europe, May 2021.

⇲ publication

  • S. Tabassum, M. B. Sampa, R. Islam, F. Yokota, N. Nakashima, A. Ahmed, "An Analysis on Remote Healthcare Data for Future Health Risk Prediction to Reduce Health Management Cost", APAMI 2020: 11th Biennial Conference of the Asia-Pacific Association for Medical Informatics, Hamamatsu, Japan, November, 2020.

⇲ publication ⇲ certificate ⇲ APAMI Bursary Award

  • S. Tabassum, M. B. Sampa, R. Islam, F. Yokota, N. Nakashima, A. Ahmed, "A Data Enhancement Approach to Improve Machine Learning Performance for Predicting Health Status Using Remote Healthcare Data", 2nd International Conference on Advanced Information and Communication Technology 2020 (ICAICT 2020), Dhaka, Bangladesh, November, 2020.

⇲ publication ⇲ certificate

  • S. Tabassum, M. S. Ullah, N. H. Al-nur, S. Shatabda, "Native Vehicles Classification on Bangladeshi Roads Using CNN with Transfer Learning", IEEE Region 10 Symposium (TENSYMP) 2020, Dhaka, Bangladesh, June 2020.

⇲ publication ⇲ certificate

  • S. Tabassum, M. I. U. Zaman, M. S. Ullah, A. Rahaman, S. Nahar and A. K. M. M. Islam, "The Cardiac Disease Predictor: IoT and ML Driven Healthcare System", 2019 4th International Conference on Electrical Information and Communication Technology (EICT), Khulna, Bangladesh, December 2019.

⇲ publication

  • M. I. U. Zaman, S. Tabassum, M. S. Ullah, A. Rahaman, S. Nahar and A. K. M. M. Islam, "Towards IoT and ML Driven Cardiac Status Prediction System", 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT), Dhaka, Bangladesh, May 2019.

⇲ publication


Undergrad Research Projects

  • Predicting Cardiac Anomaly using IoT sensors and Machine Learning

    1. Collect vital signs such as heart rate, electrocardiogram, blood pressure, blood cholesterol from the human body using sensor-based wearable technology.

    2. Trained a neural network on Cleveland dataset from the UCI Machine Learning Repository to detect and notify cardiac abnormality of a patient. The model achieved 82% accuracy.

    3. Developed a mobile app to connect with the sensors and notify the user in case any anomaly is found.

  • Bangladeshi Local Vehicles Detection and Classification Using CNN with Transfer Learning

    1. Developed a perception system to detect and classify fifteen Bangladeshi native vehicles such as rickshaw, easybike, cng, van, boat, truck, tractor, horsecart.

    2. Implemented Convolutional Neural Network (CNN) using TensorFlow.

    3. Used CFG files and pre-trained weights of 'You Only Look Once (YOLO)' algorithm to build the CNN network.

    4. Collected over 9000 images of fifteen vehicles and introduced 'Bangladeshi Vehicles Dataset'.

    5. Wrote corresponding annotation files of the images in XML using LabelImg tool.

    6. Applied Transfer Learning and trained the model for 100 epoches.

    7. Achieved 73% IoU and 3.19 average loss.

Technology stack: YOLO algorithm, TensorFlow, DarkFlow, Transfer Learning.

  • Real-time Three-wheeler Local Vehicle ‘Rickshaw’ Detection Using CNN Algorithm

    1. Developed a real-time object detection system to recognize a local three-wheeler vehicle 'Rickshaw' using the YOLO algorithm.

    2. Implemented Convolutional Neural Network using TensorFlow.

    3. Used CFG files and pre-trained weights of YOLO to build TensorFlow network.

    4. Collected 1000 images of the vehicle from Bangladeshi roads.

    5. Wrote corresponding annotation files of the images in XML using LabelImg tool.

    6. Trained the model for 50 epochs and achieved 86% accuracy.

Technology stack: YOLO algorithm, TensorFlow, DarkFlow.