Traffic Count technology is based on applied research
X. Chen, S. Yongchareon, M. Knoche, “A review on computer vision and machine learning techniques for automated road surface defect and distress detection, Journal of Smart Cities and Society, vol. 1, no. 4, pp. 259-275, 2022
J. Thumm, J. Masino, M. Knoche, F. Gauterin, M. Reischl, “A novel approach to label road defects in video data: semi-automated video analysis”, International Journal on Smart Sensing and Intelligent Systems, March 2020
S. Zuev, A. Boerner, H. Zhang, I. Ernst, M. Knoche, R. Klette, “Mobile System for Road Inspection and 3D modelling”, International Transport (71), 1 2019
I. Baumbach, H. Zhang, S. Zuev, J. Wohlfeil, M. Knoche and R. Klette, “GPS and IMU Require Visual Odometry for Elevation Accuracy”, in Proc. Advanced Video and Signal-based Surveillance, 2018
I. Ernst, H. Zhang, S. Zuev, M. Knoche, A. Dhiman, H.-J. Chien, and R. Klette, “Large-scale 3D Roadside Modelling with Road Geometry Analysis: Digital Roads New Zealand”, in Proc. Pervasive Systems, Algorithms and Networks, 2018
H. Bahrami, M. Knoche, “Rural Road Condition Prediction , “A novel IoT and neural network approach”, ITS NZ T-Tech Conference Paper 2019H. Zhang, I. Ernst, S. Zuev, A. Börner, M. Knoche, and R. Klette, “Visual odometry and 3D point clouds under low-light conditions”, in IEEE Proc. Image Vision Computing New Zealand, doi: 10.1109/IVCNZ.2018.8634769, 2018
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The revitalized Art Gallery is set to redefine the cultural landscape of Toronto, serving as a nexus of artistic expression, community engagement, and architectural marvel. The expansion and renovation project pay homage to the Art Gallery’s rich history while embracing the future, ensuring that the gallery remains a beacon of inspiration.
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