Comparing classic to state-of-the-art image features: a clustering approach using local binary patterns and ResNet-18 features for lung ultrasound video classification

Comparing classic to state-of-the-art image features: a clustering approach using local binary patterns and ResNet-18 features for lung ultrasound video classification

Files

Comparing-Classic-to-State-of-the-Art-Image-Features_Bhattacharjee.pdf(242.47 KB)

Date

2024-10-21

Authors

Bhattacharjee, Saunak

Thompson, Russell

Etter, Lauren P.

Pieciak, Rachel C.

Castro-Aragon, Ilse

Gill, Christopher C.

Version

Other

URI

https://hdl.handle.net/2144/49918

Citation

S. Bhattacharjee, U. Khan, R. Thompson, L.P. Etter, I. Camelo, R.C. Pieciak, I. Castro-Aragon, B. Setty, C.C. Gill, M. Betke. 2024. "Comparing Classic to State-of-the-Art Image Features: A Clustering Approach Using Local Binary Patterns and ResNet-18 Features for Lung Ultrasound Video Classification"

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BU Open Access Articles