Enhancing crop yield classification with SVM implementation on PYNQ Z2 for improved execution speed and efficient resource utilization

Pavani S, Augusta Sophy Beulet P

Open source

DOI: 10.1038/s41598-026-47986-6
Published: 2026-04-29
Container: Scientific Reports
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1038/s41598-026-47986-6,
  title = {Enhancing crop yield classification with SVM implementation on PYNQ Z2 for improved execution speed and efficient resource utilization},
  author = {Pavani S and Augusta Sophy Beulet P},
  year = {2026},
  journal = {Scientific Reports},
  doi = {10.1038/s41598-026-47986-6},
  url = {https://doi.org/10.1038/s41598-026-47986-6}
}

RIS

TY  - JOUR
TI  - Enhancing crop yield classification with SVM implementation on PYNQ Z2 for improved execution speed and efficient resource utilization
AU  - Pavani S
AU  - Augusta Sophy Beulet P
PY  - 2026
JO  - Scientific Reports
DO  - 10.1038/s41598-026-47986-6
UR  - https://doi.org/10.1038/s41598-026-47986-6
ER  -

APA

S, P., & P, A. S. B. (2026). Enhancing crop yield classification with SVM implementation on PYNQ Z2 for improved execution speed and efficient resource utilization. Scientific Reports. https://doi.org/10.1038/s41598-026-47986-6

Source records

crossref · retrieved 2026-09-26T02:28:08.112Z