Transfer Learning

Bridging data-rich and data-poor domains on Lithium-Ion Battery via Scanning Electron Microscopic data through Convolutional Neural Network Transfer Learning

We propose a transfer learning framework using EfficientNet-B0 to robustly classify SEM images of lithium-ion battery cathodes across compositions and aging states, effectively handling data scarcity and domain shift from electrolyte additives.

Haein Jeon, Bo-Yeong Kang, Donghun Lee, Jimin Oh

Bridging data-rich and data-poor domains on Lithium-Ion Battery via Scanning Electron Microscopic data through Convolutional Neural Network Transfer Learning