**7. Conclusions**

This chapter highlights the importance of the employment of deep learning architectures in the context of future industrial applications with a focus on welding and welding defects detection. The industrial sector and especially the manufacturing industry pose several challenges to the design of efficient and robust quality inspection processes. The most common issues are discussed in detail, and possible countermeasures are suggested to overcome such issues. In particular, the problem of data imbalance, scarcity of examples, environmental noises, change in the nominal conditions of the process, or the presence of artifacts are discussed. Application examples from previous works of the authors are proposed to clarify how the suggested countermeasures can be put into practice. Although many industries are still scared of adopting deep learning approaches due to a lack of knowledge of their internal processes or reasoning, extensive use of artificial intelligence applications is envisaged for the near future.
