Toward artificial intelligence and machine learning-enabled frameworks for improved predictions of lifecycle environmental impacts of functional materials and devices

T Ibn-Mohammed, KB Mustapha, M Abdulkareem… - MRS …, 2023 - Springer
The application of functional materials and devices (FM&Ds) underpins numerous products
and services, facilitating improved quality of life, but also constitutes a huge environmental …

An expert system for redesigning software for cloud applications

R Yedida, R Krishna, A Kalia, T Menzies, J **ao… - Expert Systems with …, 2023 - Elsevier
Cloud-based software has many advantages. When services are divided into many
independent components, they are easier to update. Also, during peak demand, it is easier …

Analyzing the performance of novel activation functions on deep learning architectures

A Chaturvedi, N Apoorva, MS Awasthi, S Jyoti… - Emerging Research in …, 2022 - Springer
Deep learning is a cutting-edge technology that functions similarly to the human nervous
system. Neural networks are at the heart of Deep Learning. Neural networks are made up of …

Hybrid synthetic data generation pipeline that outperforms real data

SA Natarajan, MG Madden - Journal of Electronic Imaging, 2023 - spiedigitallibrary.org
Fine-tuning a pretrained model with real data for a machine learning task requires many
hours of manual work, especially for computer vision tasks, where collection and annotation …

Measure or infer? Role of modeling and machine learning in modern astronomy

S Saha, N Nagaraj - The European Physical Journal Special Topics, 2021 - Springer
Theory of machine learning, deep learning in particular has been witnessing an implosion
lately in deciphering the “black-box approaches”. Optimizing deep neural networks is largely …

[CITAZIONE][C] An Empirical Study on Switching Activation Functions in Shallow and Deep Neural Networks

A Vinod, A Mathur, S Saha - International Journal of Computer and Systems …, 2023