The following paper carries out the bibliometric performance of DL applications in the arena of computer science, focusing on its growth, trends, and impacts brought about by this transformational technology during 2010–2025. The obtained data from Scopus presents the evolution of the research development on DL in the field of computer science and shows the main publication trends, the leading authors, institutions, and countries. The analysis reveals significant growth in DL research, particularly after 2015, driven by advancements in computational power, the availability of large datasets, and the development of sophisticated neural network architectures. The findings underscore the global nature of DL research, with significant contributions from China, the United States, and India. Key research areas include computer vision, natural language processing, and reinforcement learning. The study enlightens researchers, computer scientists, and policymakers on the capability of DL to solve some of the hot challenges in computer science and offers directions for future research.