Distributed intelligence for IoT-based smart cities: a survey
The remarkable miniaturization of Internet of Things (IoT)-based systems and the rise of
distributed intelligence are promising research paradigms in the design of smart cities. IoT …
distributed intelligence are promising research paradigms in the design of smart cities. IoT …
Computationally efficient neural rendering for generator adversarial networks using a multi-GPU cluster in a cloud environment
A Ravikumar, H Sriraman - IEEE Access, 2023 - ieeexplore.ieee.org
Due to its fantastic performance in the quality of the images created, Generator Adversarial
Networks have recently become a viable option for image reconstruction. The main problem …
Networks have recently become a viable option for image reconstruction. The main problem …
DPro-SM–A distributed framework for proactive straggler mitigation using LSTM
A Ravikumar, H Sriraman - Heliyon, 2024 - cell.com
The recent advancement in deep learning with growth in big data and high-performance
computing is Distributed Deep Learning. The rapid rise in the volume of data and network …
computing is Distributed Deep Learning. The rapid rise in the volume of data and network …
Secure Key Generation and Management Using Generative Adversarial Networks
The generation and control of cryptographic keys are the most important things when it
comes to the security and integrity of encrypted data. The traditional key generation methods …
comes to the security and integrity of encrypted data. The traditional key generation methods …
Evaluation of the Distributed Strategies for Data Parallel Deep Learning Model in TensorFlow
A Ravikumar, H Sriraman - Scalable and Distributed Machine …, 2023 - igi-global.com
Distributed deep learning is a branch of machine intelligence in which the runtime of deep
learning models may be dramatically lowered by using several accelerators. Most of the past …
learning models may be dramatically lowered by using several accelerators. Most of the past …