FedXAI-ISL: Explainable Artificial Intelligence-Based Federated Model in Recognition and Community Decentralized Learning of Indian Sign Language
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-3588-4_32
Reference23 articles.
1. López-Blanco R, Alonso RS, González-Arrieta A, Chamoso P, Prieto J (2023) Federated learning of explainable artificial intelligence (FED-XAI): a review. In: International symposium on distributed computing and artificial intelligence. Springer Nature Switzerland, Cham, pp 318–326
2. David D, Alamoodi AH, Albahri OS, Zaidan BB, Zaidan AA, Garfan S, Ismail AR, Albahri AS, Alsinglawi B, Malik RQ (2023) Landscape of sign language research based on smartphone apps: coherent literature analysis, motivations, open challenges, recommendations and future directions for app assessment. Universal Access in the Information Society, 1–16
3. Rahman A, Hossain MS, Muhammad G, Kundu D, Debnath T, Rahman M, Khan MS, Tiwari P, Band SS (2023) Federated learning-based AI approaches in smart healthcare: concepts, taxonomies, challenges and open issues. Cluster Comput 26(4):2271–2311
4. Saraswat D, Bhattacharya P, Verma A, Prasad VK, Tanwar S, Sharma G, Bokoro PN, Sharma R (2022) Explainable AI for healthcare 5.0: opportunities and challenges. IEEE Access
5. Bárcena JLC, Daole M, Ducange P, Marcelloni F, Renda A, Ruffini F, Schiavo A (2022) Fed-XAI: federated learning of explainable artificial intelligence models. In: 3rd Italian workshop on explainable artificial intelligence (XAI. it 2022)
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