Selecting the optimal transfer learning model for precise breast cancer diagnosis utilizing pre-trained deep learning models and histopathology images

A Ravikumar, H Sriraman, B Saleena, B Prakash - Health and Technology, 2023 - Springer
Abstract Background Every year, around 1.5 million women worldwide receive a breast
cancer diagnosis, which is why the mortality rate for women is rising. Scientists have …

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 …

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 …

Transformers as a classifier for solar flare time series: a comparative study

JS Ferreira, ALS Gradvohl, AEA da Silva, GP Coelho… - 2024 - researchsquare.com
Solar flares are violent and sudden eruptions that occur in the solar atmosphere and release
energy in the form of radiation. They can affect technological systems on Earth and in its …

Circumventing Stragglers and Staleness in Distributed CNN using LSTM

A Ravikumar, H Sriraman, S Lokesh… - … Transactions on Internet …, 2024 - publications.eai.eu
INTRODUCTION: Using neural networks for these inherently distributed applications is
challenging and time-consuming. There is a crucial need for a framework that supports a …

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 …