Coccidiosis Disease Classification using VGG-16 model with MLOps

11 pages•Published: August 6, 2024

M V Ezhil Dyana, S Rakesh and V Shyamganesh

Abstract

The development of Machine Learning (ML) and DevOps, often referred to as MLOps, has revolutionized the healthcare sector by offering efficient and scalable solutions for disease classification. Machine Learning models, particularly deep learning algorithms, have demonstrate d remarkable performance in classifying diseases from various medical data modalities such as images, genomic sequences, electronic health records, and more.

Keyphrases: mlops, vgg 16, workflow

In: Rajakumar G (editor). Proceedings of 6th International Conference on Smart Systems and Inventive Technology, vol 19, pages 333-343.

Links:	https://easychair.org/publications/paper/ftjr
	https://doi.org/10.29007/gpx5

BibTeX entry

@inproceedings{ICSSIT2024:Coccidiosis_Disease_Classification_using,
  author    = {M V Ezhil Dyana and S Rakesh and V Shyamganesh},
  title     = {Coccidiosis Disease Classification using VGG-16 model with MLOps},
  booktitle = {Proceedings of 6th International Conference on Smart Systems and Inventive Technology},
  editor    = {Rajakumar G},
  series    = {Kalpa Publications in Computing},
  volume    = {19},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {/publications/paper/ftjr},
  doi       = {10.29007/gpx5},
  pages     = {333-343},
  year      = {2024}}

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