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In this paper Quantization effects are assessed for a real time Edge based person detection use case that is based on the use of a Raspberry Pi. TensorFlow architectures are presented that enable the use of real-time person detection on the Raspberry Pi. The model quantization is performed, performance of quantized models is analyzed, and worstcase performance is established for a number of deep learning object detection models that are capable of being deployed on the Pi for realtimedblp:conf/aics/MohandasBPCH20 fatcat:5xa3x5zwozckfohem4atay7mgi