• An Adaptive Salp-Stochastic-Gradient-Descent-Based Convolutional LSTM With MapReduce Framework for the Prediction of Rainfall 

  Manoj, S. Oswalt; Kumar, Abhishek; Dubey, Ashutosh Kumar; Ananth, J. P. (UNIR, 01/09/2025)

  Rainfall prediction is considered to be an esteemed research area that impacts the day-to-day life of Indians. The predominant income source of most of the Indian population is agriculture. It helps the farmers to make the ...

• Measuring the Difference Between Pictures From Controlled and Uncontrolled Sources to Promote a Destination. A Deep Learning Approach 

  Diaz Pacheco, AngeL; Álvarez Carmona, Miguel A.; Rodríguez González, Ansel Y.; Carlos, Hugo; Aranda, Ramón (UNIR, 01/09/2025)

  Promoting a destination is a major task for Destination Marketing Organizations (DMOs). Although DMOs control, to some extent, the information presented to travelers (controlled sources), there are other different sources ...

• Performance and Communication Cost of Deep Neural Networks in Federated Learning Environments: An Empirical Study 

  Alotaibi, Basmah K.; Khan, Fakhri Alam; Qawqzeh, Yousef; Jeon, Gwanggil; Camacho, David (UNIR, 01/09/2025)

  Federated learning, a distributive cooperative learning approach, allows clients to train the model locally using their data and share the trained model with a central server. When developing a federated learning environment, ...

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