  Facing the rapid growth in the issuance of financial tickets (or bills,
invoices etc.), traditional manual invoice reimbursement and financial
accounting system are imposing an increasing burden on financial accountants
and consuming excessive manpower. To solve this problem, we proposes an
iterative self-learning Framework of Financial Ticket intelligent Recognition
System (FFTRS), which can support the fast iterative updating and extensibility
of the algorithm model, which are the fundamental requirements for a practical
financial accounting system. In addition, we designed a simple yet efficient
Financial Ticket Faster Detection network (FTFDNet) and an intelligent data
warehouse of financial ticket are designed to strengthen its efficiency and
performance. At present, the system can recognize 194 kinds of financial
tickets and has an automatic iterative optimization mechanism, which means,
with the increase of application time, the types of tickets supported by the
system will continue to increase, and the accuracy of recognition will continue
to improve. Experimental results show that the average recognition accuracy of
the system is 97.07%, and the average running time for a single ticket is
175.67ms. The practical value of the system has been tested in a commercial
application, which makes a beneficial attempt for the deep learning technology
in financial accounting work.
