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Integrating AI techniques into connected autonomous vehicles (CAVs) and unmanned aerial vehicles (UAVs) and their data fusion, enables a new paradigm that allows for unparalleled real-time awareness of the surrounding environment. The potential of emerging wireless technologies can be fully exploited by establishing communication and cooperation among AI-augmented CAVs and UAVs. However, configuring appropriate deep learning (DL) models for connected vehicles is a complex task. Any errors can result in severe consequences, including loss of vehicles, infrastructure, and human lives. These systems are also susceptible to cyber attacks, necessitating a thorough and timely threat analysis and countermeasures to prevent catastrophic events. Our findings highlight the effectiveness of AI-driven data fusion in enhancing cooperative perception between CAVs and UAVs, identify security vulnerabilities in DL-based systems, and demonstrate how V2X-enabled UAVs can significantly improve situational awareness in corner cases.<\/jats:p>","DOI":"10.1007\/s10462-025-11425-1","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T05:20:44Z","timestamp":1763616044000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Unifying ground and air: a comprehensive review of deep learning-enabled CAVs and UAVs"],"prefix":"10.1007","volume":"59","author":[{"given":"Muhammad Umer","family":"Zia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Xiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jameel","family":"Ahmad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4444-6306","authenticated-orcid":false,"given":"Jawwad Nasar","family":"Chattha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ijaz Haider","family":"Naqvi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Faran Awais","family":"Butt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,20]]},"reference":[{"key":"11425_CR1","unstructured":"Abbasi M, Gagn\u00e9 C (2017) Robustness to adversarial examples through an ensemble of specialists. arXiv preprint arXiv:1702.06856"},{"key":"11425_CR2","unstructured":"Abir MABS, Chowdhury MZ, Jang YM (2023) Software-defined UAV networks for 6G systems: requirements, opportunities, emerging techniques, challenges, and research directions. 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