Abstract: Some embodiments of the present disclosure relate to a processing tool. The tool includes a housing enclosing a processing chamber, and an input/output port configured to pass a wafer through the housing into and out of the processing chamber. A back-side macro-inspection system is arranged within the processing chamber and is configured to image a back side of the wafer. A front-side macro-inspection system is arranged within the processing chamber and is configured to image a front side of the wafer according to a first image resolution. A front-side micro-inspection system is arranged within the processing chamber and is configured to image the front side of the wafer according to a second image resolution which is higher than the first image resolution.

Abstract: A digital artificial neural network (ANN) reduces memory requirements by storing sample transfer function representing output values for multiple nodes. Each nodes receives an input value representing the information to be processed by the network. Additionally, the node determines threshold values indicative of boundaries for application of the sample transfer function for the node. From the input value received, the node generates an intermediate value. Based on the threshold values and the intermediate value, the node determines an output value in accordance with the sample transfer function.