GastroNet: A Custom Deep Learning Approach for Classification of Anomalies in Gastrointestinal Endoscopy Images.

Mary A A, Raj A PW, Karthik C, Karunaharan A

DOI: 10.2174/1573405620666230906092310
Published: 2024
Container: Current medical imaging
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.2174/1573405620666230906092310,
  title = {GastroNet: A Custom Deep Learning Approach for Classification of Anomalies in Gastrointestinal Endoscopy Images.},
  author = {Mary A A and Raj A PW and Karthik C and Karunaharan A},
  year = {2024},
  journal = {Current medical imaging},
  doi = {10.2174/1573405620666230906092310},
  url = {https://doi.org/10.2174/1573405620666230906092310}
}

RIS

TY  - JOUR
TI  - GastroNet: A Custom Deep Learning Approach for Classification of Anomalies in Gastrointestinal Endoscopy Images.
AU  - Mary A A
AU  - Raj A PW
AU  - Karthik C
AU  - Karunaharan A
PY  - 2024
JO  - Current medical imaging
DO  - 10.2174/1573405620666230906092310
UR  - https://doi.org/10.2174/1573405620666230906092310
ER  -

APA

A, M. A., PW, R. A., C, K., & A, K. (2024). GastroNet: A Custom Deep Learning Approach for Classification of Anomalies in Gastrointestinal Endoscopy Images.. Current medical imaging. https://doi.org/10.2174/1573405620666230906092310

Source records

pubmed · retrieved 2026-09-26T18:54:21.113Z