Architected sensing systems for intelligent ambient sensing.
Defined sensing theory of operations and requirements.
Led cross-functional sensing HW and SW developments.
Managed system development from prototype to product.
Assessed critical emerging technologies for future products.
Architected sensing systems for higher level autonomy.
Defined sensing theory of operations and requirements.
Led cross-functional sensing HW and SW developments.
Managed system development from prototype to product.
Assessed critical emerging technologies for future products.
Detecting and Classifying Anomalies in Artificial Intelligence Systems, US20220327389A1 (US Patent), WO2021046300A1(WIPO Patent).
Variance of Gradient based Active Learning Framework for Training Perception Algorithms, US12079738B2 (US Patent), DE102022102929A1 (Germant Patent), CN114943264A (China Patent).
Traffic Sign Detection Dataset - Partially Simulated: https://youtu.be/8V1LcpDlmjA
Traffic Sign Detection Dataset - Fully Simulated: https://youtu.be/bKnlJ_EWS8Q
D. Temel, M-H. Chen, and G. AlRegib, “Traffic Sign Detection under Challenging Conditions: A Deeper Look Into Performance Variations and Spectral Characteristics,” the IEEE Transactions on Intelligent Transportation Systems, 2019, [Dataset], [GitHub], [arXiv].
D. Temel, T. AlShawi, M-H. Chen, and G. AlRegib, “Challenging Environments for Traffic Sign Detection: Reliability Assessment under Inclement Condition,” February 2019, [Dataset], [GitHub], [arXiv].
D. Temel and G. AlRegib, “Traffic Signs in the Wild: Highlights from the IEEE Video and Image Processing Cup 2017 Student Competition [SP Competitions],” in IEEE Signal Processing Magazine, vol. 35, no. 2, pp. 154-161, March 2018, [Dataset], [GitHub], [arXiv].
G. Kwon, M. Prabhushankar, D. Temel, and G. AlRegib, “Backpropagated Gradient Representations for Anomaly Detection ,” the European Conference on Computer Vision
C. Lehman, D. Temel, and G.AlRegib, “On The Structures of Representation for The Robustness of Semantic Segmentation to Input Corruption,” the IEEE International Conference on Image Processing, 2020, [IEEE], [GitHub].
C. Lehman, D. Temel, and G. AlRegib, “Implicit Background Estimation for Semantic Segmentation,” the IEEE International Conference on Image Processing, Taipei, Taiwan, September 2019, [GitHub], [arXiv].
D.Temel, G. Kwon, M. Prabhushankar, and G. AlRegib, “CURE-TSR: Challenging Unreal and Real Environments for Traffic Sign Recognition,” 31st Conference on Neural Information Processing Systems (NeurIPS), Machine Learning for Intelligent Transportation Systems Workshop, Long Beach, CA, USA, 2017, [Dataset], [GitHub], [arXiv].
Ocular Monitoring Headset Patent: US11185224B2 (US Patent).
Transfer Learning for Medical Applications Using Limited Data: US12159229B2 (US Patent), WO2020243460A1 (WIPO).
D. Temel, M. J. Mathew, G. AlRegib, and Y. M. Khalifa, “Automated Relative Afferent Pupillary Defect Screening in a Controlled Environment,” the IEEE Journal of Biomedical and Health Informatics, March 2020, [GitHub], [arXiv], Selected as the Cover of the Journal.
D. Temel, M. J. Mathew, G. AlRegib, and Y. M. Khalifa, “Automated Papillary Light Reflex Assessment on a Portable Platform,” the IEEE International Symposium on Medical Robotics, Atlanta, GA, April 2019, [GitHub], [arXiv].
D. Temel and G. AlRegib, “Perceptual Image Quality Assessment through Spectral Analysis of Error Representations ,” Signal Processing: Image Communication, Volume 70, 2019, Pages 37-46, [GitHub], [arXiv]
D. Temel and G. AlRegib, “CSV: Image quality assessment based on color, structure, and visual system,” Signal Processing: Image Communication, vol. 48, pp. 92-103, October 2016, [GitHub], [arXiv].
D. Temel, M. Prabhushankar and G. AlRegib, “UNIQUE: Unsupervised Image Quality Estimation”, the IEEE Signal Processing Letters , vol.23, no.10, pp.1414-1418, [GitHub], [arXiv]
M. Prabhushankar, D. Temel, and G. AlRegib, “Generating Adaptive and Robust Filter Sets Using an Unsupervised Learning Framework”, the IEEE International Conference on Image Processing, Beijing, China, Sept. 17 – Sept. 20, 2017, [GitHub], [arXiv].
M. Prabhushankar, D. Temel, and G. AlRegib, “MS-UNIQUE: Multi-model and Sharpness-weighted Unsupervised Image Quality Estimation”, the Electronic Imaging, Image Quality and System Performance XIV, Burlingame, California, USA, Jan. 29 – Feb. 2, 2017, [GitHub], [arXiv].
D. Temel and G. AlRegib, “Boosting in Image Quality Assessment”, the IEEE Workshop on Multimedia Signal Processing, Montreal, Canada, September 21-23, 2016, [GitHub], [arXiv].
D. Temel and G. AlRegib, “ReSIFT: Reliability-weighted SIFT-based Image Quality Assessment”, the IEEE International Conference on Image Processing, Phoenix, Arizona, USA, Sep. 25-28, 2016, [GitHub], [arXiv].
D. Temel and G. AlRegib, “BLeSS: Bio-inspired Low-level Spatiochromatic Similarity Assisted Image Quality Assessment “, the IEEE International Conference on Multimedia and Expo , Seattle, USA, Jul. 11-15, 2016, [GitHub], [arXiv].
J. Sogaard, L. Krasula, M. Shahid, D. Temel, K. Brunnstorm, and M. Razaak, “Applicability of Existing Objective Metrics of Perceptually Quality for Adaptive Video Streaming,” Image Quality and System Performance – EI, San Francisco, Feb. 14-18, 2016. [Imaging].
D. Temel and G. AlRegib, “A Comparative Study of Quality and Content-based Spatial Pooling Strategies in Image Quality Assessment,” the 3rd IEEE Global Conference on Signal and Information Processing , Orlando, Florida, Dec. 14-16, 2015, [GitHub], [arXiv].
D. Temel and G. AlRegib, “PerSIM: Multi-Resolution Image Quality Assessment in the Perceptually Uniform Color Domain,” in the Proceedings of the IEEE International Conference on Image Processing ,Quebec, Canada, Sept. 27-30, 2015, [GitHub], [arXiv].
D. Temel and G. AlRegib, “Image Quality Assessment and Color Difference,” in the Proceedings of the 2nd IEEE Global Conference on Signal and Information Processing, Atlanta, USA, Dec. 3-5, 2014, [GitHub], [arXiv].
D. Temel and G. AlRegib, “A Comparative Study of Computational Aesthetics,” in the Proceedings of the IEEE International Conference on Image Processing, Paris, France, Oct. 27-30, 2014, [arXiv].
D. Temel and G. AlRegib, “Coding of 3D Videos based on Visual Discomfort,” in the Proceedings of the the 47th Asilomar Conference on Signals, Systems and Computers ,Pacific Grove, CA, Nov. 3-6, 2013, [arXiv].
D. Temel, Q. Lin, G. Zhang and G. AlRegib, ” Modified Weak Fusion Model for Depthless Streaming of 3D Videos,” in the Proceedings of the IEEE International Workshop on Hot Topics in 3D, San Jose, CA, July. 19, 2013, [IEEE].
D. Temel and G. AlRegib, “Effectiveness of 3VQM in Capturing Depth Inconsistencies,” in the Proceedings of the 11th IEEE IVMSP Workshop : 3D Image/Video Technologies and Applications , Seoul, Korea, Jun. 10-12, 2013, [arXiv].
D. Temel, M. Aabed, M. Solh and G. AlRegib, “Efficient Streaming of Stereoscopic Depth-Based 3D Videos,” in the Proceedings of the Visual Information Processing and Communication IV, SPIE Electronic Imaging, San Francisco, US, Feb. 3-7, 2013, [SPIE].
M. Aabed, D. Temel, and G. AlRegib, “Depth Map Estimation in DIBR Stereoscopic 3D Videos Using a Combination of Monocular Cues,” in the Proceedings of the 46th Asilomar Conference on Signals and Systems, CA, Nov. 4-7, 2012.
D. Temel and G. AlRegib, “Depthless Streaming of Depth-Based 3D Videos,” in the Proceedings of the IEEE International Workshop on Multimedia Signal Processing (MMSP 2012), Banff, Canada, Sept. 17-19, 2012.
No technical publications due to confidentiality
$9M Smart TV project between Korea and US
Funded by Korean Industrial Tech Foundation
Bumblebee and Kinect sensors used for demo
CV-based gesture recognition for user control
Link: https://www.newswise.com/articles/korean-government-and-georgia-tech-form-partnership