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==Test Bed==
The following table details the test bed used for this Technical Note.{| class="wikitable" style="margin: auto;"|+Host and target configurations!System!Component!Name!Version!Notes|-| rowspan="3" |'''Host'''|Operating system|GNU/Linux Ubuntu|18.04||-|Software development platform|Vitis|1.2||-|Machine learning frameworl|TensorFlow|1.15.2||-| rowspan="4" |'''Target'''|Hardware platform|ZCU104|1.0||-|Linux BSP|Petalinux|2020.1||-|Software binary image (microSD card)|xilinx-zcu104-dpu-v2020.1-v1.2.0|v2020.1-v1.2.0||-|Neural network hardware accelerator|DPU|3.3|For more details, please refer to the following sections.|}
==FICS-PCB dataset overview==
Over the years, computer vision and ML disciplines have considerably advanced the field of Automated Visual Inspection for Printed Circuit Board (PCB-AVI) assurance. It is already well-known that to develop a robust model
