Articles | Volume 3, issue 1
J. Sens. Sens. Syst., 3, 113–120, 2014
https://doi.org/10.5194/jsss-3-113-2014

Special issue: 11th International Symposium on Measurement Technology and...

J. Sens. Sens. Syst., 3, 113–120, 2014
https://doi.org/10.5194/jsss-3-113-2014

Regular research article 03 Jun 2014

Regular research article | 03 Jun 2014

Work area monitoring in dynamic environments using multiple auto-aligning 3-D sensors

Y. Wang et al.

Related subject area

Measurement systems: Sensor signal processing and electronics
Smart in-cylinder pressure sensor for closed-loop combustion control
Dennis Vollberg, Peter Gibson, Günter Schultes, Hans-Werner Groh, and Thomas Heinze
J. Sens. Sens. Syst., 11, 1–13, https://doi.org/10.5194/jsss-11-1-2022,https://doi.org/10.5194/jsss-11-1-2022, 2022
Short summary
Efficient transient testing procedure using a novel experience replay particle swarm optimizer for THD-based robust design and optimization of self-X sensory electronics in industry 4.0
Qummar Zaman, Senan Alraho, and Andreas König
J. Sens. Sens. Syst., 10, 193–206, https://doi.org/10.5194/jsss-10-193-2021,https://doi.org/10.5194/jsss-10-193-2021, 2021
Short summary
Intelligent fault detection of electrical assemblies using hierarchical convolutional networks for supporting automatic optical inspection systems
Alida Ilse Maria Schwebig and Rainer Tutsch
J. Sens. Sens. Syst., 9, 363–374, https://doi.org/10.5194/jsss-9-363-2020,https://doi.org/10.5194/jsss-9-363-2020, 2020
Short summary
Measurement uncertainty analysis of field-programmable gate-array-based, real-time signal processing for ultrasound flow imaging
Richard Nauber, Lars Büttner, and Jürgen Czarske
J. Sens. Sens. Syst., 9, 227–238, https://doi.org/10.5194/jsss-9-227-2020,https://doi.org/10.5194/jsss-9-227-2020, 2020
Short summary
Compilation of training datasets for use of convolutional neural networks supporting automatic inspection processes in industry 4.0 based electronic manufacturing
Alida Ilse Maria Schwebig and Rainer Tutsch
J. Sens. Sens. Syst., 9, 167–178, https://doi.org/10.5194/jsss-9-167-2020,https://doi.org/10.5194/jsss-9-167-2020, 2020
Short summary

Cited articles

Aldoma, A. and Vincze, M.: CAD-Model Recognition and 6DOF Pose Estimation Using 3D Cues, IEEE International Conference on Computer Vision Workshops, 585–592, 2011.
Belongie, S., Malik, J., and Puzicha, J.: Shape matching and object recognition using shape contexts, IEEE T. Pattern Anal., 24, 509–522, 2002.
Bennamoun, M. and Mamic, G. J.: Object recognition: fundamentals and case studies, London, Springer, 2002.
Bicego, M., Castellani, U., and Murino, V.: A hidden Markov model approach for appearance-based 3D object recognition, Pattern Recognition, 26, 2588–2599, 2005.
Bradski, G. and Kaehler, A.: Learning OpenCV: Computer Vision with the OpenCV Library, O'Reilly, 378–386, 2008.