| Autors: Neshov, N. N., Manolova, A. H., Ivanov, A. S., Tonchev K. Title: SUPPORTING BUSINESS MODEL INNOVATION BASED ON DEEP LEARNING SCENE SEMANTIC SEGMENTATION Keywords: Deep learning; semantic segmentation; teleconference; busine Abstract: The capacity to create innovative Business Models has become the foundation for numerous businesses. Business Model Innovation grows more significant as digitalization influences our everyday lives and prompts the development of better approaches for working, imparting and collaborating in this computerized universe of Industry 4.0. In this paper we present a conceptual architecture which can be applied in the modern video-conference systems with the help of semantic segmentation. The scene represents an environment, intended for discussion of ideas in business modeling. The semantic segmentation allows each pixel of an image (or video) from the scene to be related or classified to a specific type of object. In this way it is possible to interpret the description of a scene by the machine. Thus, with the help of the proposed architecture, the processes taking place between objects and people in the surrounding environment can be analyzed for the purpose of digitization of BMI. References Issue
Copyright Indian Journal of Computer Science and Engineering (IJCSE) Full text of the publication |
Цитирания (Citation/s):
1. Lv, C., Wang, Y., & Ma, Y. (2022). Construction of business innovation model for sports industry using a deep learning algorithm. Soft Computing, 1-11. - 2022 - в издания, индексирани в Scopus или Web of Science
Вид: статия в списание, публикация в реферирано издание, индексирана в Scopus
