Description
Computer vision and machine learning algorithms are often used for quality control for industrial products. Nowadays, neural networks can perform very well to detect the desired objects. Sometimes, the system has limited resources and is not capable of processing complex algorithms or use neural networks. Here, simpler algorithms are used for shape or object detection. The scope of the present work is to even lower the complexity of the shape matching algorithm by converting a shape detection algorithm to an integer version and evaluate the results. This allows to remove floating-point units (FPU) of processors and reduce the area of a System-on-Chip (SoC) design of a smart image sensor.Period | 23 Aug 2021 → 25 Aug 2021 |
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Event title | 16th IEEE Sensors Applications Symposium: SAS 2021 |
Event type | Conference |
Sponsors | IEEE, IEEE - Institute of Electrical and Electronics Engineers |
Location | Virtual, Sundsvall, SwedenShow on map |
Degree of Recognition | International |
Documents & Links
Related content
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Publications
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Evaluation of an Integer Optimized Shape Matching Algorithm
Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
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Activities
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16th IEEE Sensors Applications Symposium
Activity: Participation in or organisation of › Conference or symposium (Participation in/Organisation of)