Research

Welcome to visit my research page. Alongside research, visit this page for more about me (shahinur).

Topic: Immersive Learning, Virtual reality, Human-Computer Interaction, artificial intelligence, 3D Avatar

  • Developed a VR-based platform for immersive American Sign Language (ASL) learning.
  • Incorporated real-time feedback using motion capture technology and deep learning models.
  • Utilized Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks for sign recognition and feedback.
  • Achieved 90.12% training accuracy and 86.66% test accuracy in recognizing ASL signs.
  • Created a virtual coffee shop environment where users interact with a signing avatar to improve accuracy.
  • Made ASL education more accessible and engaging, especially for those with limited access to traditional instruction.

Tools and Technology: Oculus Quest 2 and 3, Python, Unreal Engine

Topic: Human-Computer Interaction, 3D computer vision, Gesture recognition

  • Implemented a character recognition system using finger-joint tracking and a 3-D depth camera to enhance human-computer interaction (HCI).Allowed users to write characters, digits, and symbols in mid-air using simple hand gestures.
  • Overcame the limitations of traditional gesture recognition systems by eliminating the need for wearable devices and supporting a full set of 124 characters, including digits, alphabets, symbols, and special keys.
  • Utilized the Intel RealSense SR300 camera to track 22 finger joints for precise recognition in both single-hand and double-hand modes.
  • Employed Euclidean distance thresholding and geometric slope techniques to achieve over 91% accuracy with a recognition time of less than 60 milliseconds per character.
  • Operated effectively in both light and dark environments, suitable for real-time applications.
  • Minimal training required for users, confirmed by user studies, making it a user-friendly and versatile system.
  • Potential applications include virtual reality, healthcare, and accessibility, offering a hands-free input solution across various industries.

Tools and Technology: Intel Real sense sr300 camera, C#, C

Topic: Human-Computer Interaction, 3D computer vision, Gesture recognition, Deep Learning, Recurrent neural network

  • Developed a highly accurate air-writing recognition system using deep learning and depth sensor technology.
  • Captured finger movements as 3D trajectories using Intel RealSense SR300 camera.
  • Applied normalization techniques to eliminate noise and ensure smoother trajectory data.
  • Employed Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN) for digit recognition.
  • Trained on a self-collected dataset of 21,000 trajectories and the 6D Motion Gesture (6DMG) dataset.
  • Achieved 99.32% accuracy with the LSTM model and 99.26% accuracy with the CNN model.
  • Overcame limitations of traditional writing systems by providing a touchless input method.
  • Potential applications include augmented reality (AR), virtual reality (VR), and healthcare.
  • Developed a large public dataset and integrated advanced neural network architectures to enhance recognition accuracy.

Tools and Technology: CNN, LSTM, Intel Realsense sr300 camera, C#, Matplotlib, Python

Topic: Image Processing, Computer vision, Deep Learning, Generative network, Image super-resolution, Elemental Image

  • Developed a GAN-based super-resolution algorithm to enhance the resolution of integral imaging microscopy (IIM) images by up to 8×.Addressed resolution limitations caused by the micro-lens array (MLA) and poor lighting conditions in IIM.
  • Designed a GAN model with a generator to reconstruct high-resolution images and a discriminator to distinguish real from generated images.
  • Applied the method to various microscopic specimens, including biological samples and electronic components, achieving significant improvements in clarity, detail, and depth.
  • Trained the model using PyTorch on a high-performance computing system.
  • Tested the system with metrics like PSNR, SSIM, and PSD, demonstrating superior performance compared to traditional resolution enhancement techniques.
  • Provided a scalable, efficient solution for real-time image enhancement in IIM with applications in biomedical science, nanophysics, and other fields requiring precise 3D imaging.

Tools and Technology: CNN, GAN, Integral imaging microscope, Python

Topic: Image Processing, Computer vision, Deep Learning, Residual dense network, Image super-resolution

  • Developed a Residual Dense Network (RDN) for mapping low-resolution images to high-resolution outputs.
  • Integrated guided filters to refine chromatic channels and enhance image sharpness.
  • Used bicubic interpolation for chromatic channels and SR luminance channels for detailed image enhancement.
  • Outperformed traditional methods in PSNR and visual quality on benchmark datasets.
  • Achieved faster processing speeds while maintaining high-quality image reconstruction.
  • Demonstrated improved restoration of textures and edges, making it efficient for real-time applications.

Tools and Technology: CNN, Residual net, Guided filter, Matlab

SCI(E) Journal Paper

  1. M.S. Alam, J, Lamberton, J. Wang, C. Leannah, S. Miller, J. Palagano, M. D. Bastion, H.L. Smith, M. Malzkuhn, L.C. Quandt, ASL champ!: a virtual reality game with deep-learning driven sign recognition, Computers & Education: X Reality. doi:10.1016/j.cexr.2024.100059.
  2. Rupali, S, Alam, M.S, Hossain, M.B, Imtiaz, S.M, Kim, J.H, Padwal, A.A, Kim, N. Precise Skin Cancer Detection Model for Low Computing Devices by Transfer Learning, Cancers doi:10.3390/cancers15010012.
  3. Alam, M.S, Kwon, K.C, Kim, N. TARNet: An Efficient and Lightweight Trajectory-Based Air-Writing Recognition Model Using a CNN and LSTM Network, Human Behavior and Emerging Technologies. doi:10.1155/2022/6063779.
  4. Imtiaz, S.M, Kwon, K.C, Hossain, M.B, Alam, M.S, Jeon, S.H, Kim, N. Depth Estimation for Integral Imaging Microscopy Using a 3D–2D CNN with a Weighted Median Filter, Sensors. doi:10.3390/s22145288.
  5. Rupali, S, Alam, M.S, Park, S.G,Park, S.M, Kim, N. Intelligent IoT (IIoT) Device to Identifying Suspected COVID-19 Infections Using Sensor Fusion Algorithm and Real-Time Mask Detection Based on the Enhanced MobileNetV2 Model, Healthcare. doi:10.3390/healthcare10030454.
  6. Imtiaz, S.M, Kwon, K.C, Alam, M.S, Hossain, M.B, Changsup, N, Kim, N. Identification and Correction of Microlens-array Error in an Integral-imaging-microscopy System, Current Optics and Photonics Journal. doi:10.3807/COPP.2021.5.5.524.
  7. M. S. Alam, K. -C. Kwon and N. Kim, “Implementation of a Character Recognition System Based on Finger-Joint Tracking Using a Depth Camera,” in IEEE Transactions on Human-Machine Systems, vol. 51, no. 3, pp. 229-241, June 2021, doi: 10.1109/THMS.2021.3066854.
  8. M. S. Alam, K. -C. Kwon, M. -U. Erdenebat, M. Y. Abbass; M. A. Alam, and N. Kim, “Super-Resolution Enhancement Method Based on Generative Adversarial Network for Integral Imaging Microscopy” in Sensors 2021, 21, 2164. https://doi.org/10.3390/s21062164.
  9. M. Y. Abbass, K. -C. Kwon., M. S. Alam et al. “Image super resolution based on residual dense CNN and guided filters,” in Multimed Tools Appl 80, 5403–5421 (2021). https://doi.org/10.1007/s11042-020-09824-3
  10. M.S. Alam, K.-C. Kwon; M.A. Alam, M.Y. Abbass, S.M. Imtiaz, N. Kim, “Trajectory-Based Air-Writing Recognition Using Deep Neural Network and Depth Sensor,” in Sensors 2020, 20, 376. https://doi.org/10.3390/s20020376
  11. Y. Zhao, M. -U. Erdenebat, M. S. Alam, M. -L. Piao, S. -H. Jeon, and N. Kim, “Multiple-camera holographic system featuring efficient depth grids for representation of real 3D objects,” Appl. Opt. 58, A242-A250 (2019)

Peer-reviewed Conference Paper

  1. Alam, M.S, Palagano, J, Quandt, L.C. Insights from Immersive Learning: Using Sentiment Analysis and Real-time Narration to Refine ASL Instruction in Virtual Reality, The 26th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’24). October 27–30, 2024, St. John’s, NL, Canada. doi:10.1145/3663548.3688503.
  2. Alam, M.S, Bastion, M. D, Malzkuhn, M, Quandt, L.C. ASL Champ: A new dimension of learning American Sign Language in Virtual Reality, The 31st IEEE conference on virtual reality and 3D user interfaces. workshop on Inclusion, Diversity, Equity, Accessibility, Transparency and Ethics in XR (IDEATExR).
  3. Alam, M.S, Bastion, M. D, Malzkuhn, M, Quandt, L.C. Recognizing Highly Variable American Sign Language in Virtual Reality, 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing. doi:10.17605/OSF.IO/9JM3C.
  4. Nyamsuren, D, Erdenebat, M.U, Alam, M.S, Hossain, M.B, Gil, S.K, jeong, J.R, Kim, N. Economical and Wearable Pulse Oximeter using IoT, 16th International Conference on Computer Science and Education (ICCSE). doi:10.1117/12.2610427
  5. Kim, N, Erdenebat, M.U, Wu, H.Y, Khuderchuluun, A, Nyamsuren, D, Khuderchuluun, A, Kwon, K.C, Imtiaz, S.M, Alam, M.S. Recent researches on HUD HMD using HOE and 3D integral imaging microscope (Plenary), The 11th Japan-Korea Workshop on Digital Holography & Information Photonics (DHIP 2021).
  6. Hossain, M.B, Imtiaz, S.M, Alam, M.S, Rupali, S, Kim, N. Dual-domain MRI reconstruction using CNN-GAN networks removing aliasing and blurring artifacts,Photonics Conference 2021 (PC 2021).
  7. M.S. Alam, M.U. Erdenebat, Y.T. Lim, A. Khuderchuluun, J.H. Kim, E. Dashdavaa, S.K. Gil, J.R. jeong, N. Kim, Deep Learning-Based Resolution Enhancement Method for Integral Imaging Microscopy, SPIE Advanced Biophotonics Conference.
  8. M. S. Alam, J. H. Kim, J. K. jung, Y. -T. Lim, M. B. Hossain, K. -Y. Lee, Y. -J. Yoo, and N. Kim, ” Touchless User Interactive High-Resolution Light Field Display System Using a Three-Dimensional Tracking Camera,” in the 21st International Meeting on Information Display, August 2021.
  9. S. Rupali, M. S. Alam, M. Choi, and N. Kim, ” Economical and Wearable Pulse Oximeter using IoT,” in the 16th International Conference on Computer Science & Education (ICCSE), August 2021.
  10. M. S. Alam, K. -C. Kwon, S. M. Imtiaz, M. B. Hossain, S. Rupali, J. H. Kim, and N. Kim, “Air-writing recognition using a fusion CNN-LSTM network,” in the 8th International Conference on Electronics, Electrical Engieering, Computer Scicence : Innovationa and Convergence (8th EEECS 2021), July 2021.
  11. M. S. Alam, M. -U. Erdenebat, J. K. Jung, J. H. Kim, M. B. Hossain, S. -K. Gil, and N. Kim, ” Three-dimensional head tracking based interactive light field display system using a movable camera array,” in the 28th Conference on Optoelectronics and Optical Communications (COOC 2021), June 2021.
  12. M. S. Alam, K. -C. Kwon, S. M. Imtiaz, J. -K. Pan, J. -R. Jeong, N. Kim, “User interactive high-resolution multi-view display system using a three-dimensional head-tracking camera,” Proc. SPIE 11708, Advances in Display Technologies XI, 117080E (5 March 2021); https://doi.org/10.1117/12.2578331
  13. M. S. Alam, Y. -T. Lim, J. -K. Pan, and N. Kim, “Interactive Three-Dimensional Multiview Display System Using a Head Tracking Camera,” in the 20th International Meeting on Information Display, August 2020.
  14. M. S. Alam, K. -C. Kwon, M. -C. Erdenebat, Y. -T. Lim, S. M. Imtiaz, M. A. Sufian, S. Jeon, and N. Kim, “Resolution Enhancement of an Integral Imaging Microscopy Using Generative Adversarial Network,” in 14th Pacific Rim Conference on Lasers and Electro-Optics (CLEO PR 2020), OSA Technical Digest (Optical Society of America, 2020), paper C3G_4.
  15. M. A. Alam, F. N. Khan, A. H. Khan, A. Jannat, N. E. Nisa, M. S. Alam, N. Kim, “Real-time content creation and transmission of a 3D Internet TV system based on integral imaging using GPU parallel processing,” Proc. SPIE 11304, Advances in Display Technologies X, 113040F (13 April 2020); https://doi.org/10.1117/12.2547115
  16. Y. -L. Piao, M. S. Alam, E. Dashdavaa, S. -K. Gil, K. -Y. Lee, N. Kim, “Generation speed enhancement for full color computer generated holography using multiple wave-front recording planes,” Proc. SPIE 11306, Practical Holography XXXIV: Displays, Materials, and Applications, 113060X (21 February 2020); https://doi.org/10.1117/12.2548610
  17. M. S. Alam, K. -C. Kwon and N. Kim, “Trajectory-Based Air-Writing Character Recognition Using Convolutional Neural Network,” in 4th International Conference on Control, Robotics and Cybernetics (CRC), 2019, pp. 86-90, doi: 10.1109/CRC.2019.00026
  18. M. S. Alam, K. -C. Kwon, M. -U. Erdenebat, Y. Piao, and N. Kim, ” Centralized Server-based Light Field Display System Using a Head Tracking Camera,” in the 7th International Conference on Big Data Applications and Services, Jeju, South Korea, August 2019.
  19. M. A. Alam, M. Subhani, M. S. Islam, M. Z. Tareque, M. R. R. Rafi, M. S. Alam, N. Kim, “Faster computation of elemental image generation for real-time integral imaging 3D display system using graphics processing unit and multi-directional projection scheme,” Proc. SPIE 10942, Advances in Display Technologies IX, 109420O (13 March 2019); https://doi.org/10.1117/12.2509716
  20. M. A. Alam, A. H. Khan, F. N. Khan, N. E. Nisa, A. Jannat, M. S. Alam, N. Kim, “Glass-free 3D internet TV system using integral imaging,” Proc. SPIE 10942, Advances in Display Technologies IX, 109420N (13 March 2019); https://doi.org/10.1117/12.2506703
  21. M. -U. Erdenebat, M. S. Alam, K. -C. Kwon, K. H. Kwon, M. Y. Kim, S. -K. Gil, N. Kim, “Resolution-enhanced mobile three-dimensional display based on computer-generated integral imaging,” Proc. SPIE 10942, Advances in Display Technologies IX, 109420P (1 March 2019); https://doi.org/10.1117/12.2510928
  22. Y. Zhau, M. S. Alam; S. -H. Jeon, N. Kim” Fast calculation method for full-color computer-generated hologram with real objects captured by a depth camera,” Electronic Imaging, Stereoscopic Displays and Applications XXIX, pp. 250-1-250-6(6); https://doi.org/10.2352/ISSN.2470-1173.2018.04.SDA-250
  23. Y. Zhao, M. Islam, S. Alam, S. Jeon, and N. Kim, “Rapid calculation of full-color holographic system with real objects using relocated point cloud gridding method,” in Imaging and Applied Optics 2018 (3D, AO, AIO, COSI, DH, IS, LACSEA, LS&C, MATH, pcAOP), OSA Technical Digest (Optical Society of America, 2018), paper JTu4A.2.
  24. M. S. Alam, K. -C. Kwon, Y. Zhao, M. A. Alam, and N. Kim, ” Hand Finger-Joint Tracking Based Digit Recognition,” in the International Conference on Convergence Content 2017.
  25. M. A. Alam, M. S. Islam, M. Z. Tareque, M. Subhani, M. R. R. Rafi, M. S. Alam, N. Kim, “Viewing angle enhancement of a real-time integral imaging system using multi-directional projections and GPU parallel processing,” Proc. SPIE 10126, Advances in Display Technologies VII, 101260C (16 February 2017); https://doi.org/10.1117/12.2251360