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A residual neural network (also referred to as a residual network or ResNet) [1] is a deep learning architecture in which the layers learn residual functions with reference to the layer inputs. It was developed in 2015 for image recognition , and won the ImageNet Large Scale Visual Recognition Challenge ( ILSVRC ) of that year.
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The Ford–Fulkerson method or Ford–Fulkerson algorithm (FFA) is a greedy algorithm that computes the maximum flow in a flow network.It is sometimes called a "method" instead of an "algorithm" as the approach to finding augmenting paths in a residual graph is not fully specified [1] or it is specified in several implementations with different running times. [2]
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Invoice processing : involves the handling of incoming invoices from arrival to payment. Invoices have many variations and types. In general, invoices are grouped into two types: Invoices associated with a company's internal request or purchase order (PO-based invoices) and; Invoices that do not have an associated request (non-PO invoices).