Estimating Nutritional Composition from Food Volume Via Deep Learning-Based Depth and Segmentation Models

Anh Le, Anh Do, Thanh Nguyen, Binh Nguyen, An Tran, Nha Tran

Open source

DOI: 10.9734/ajrcos/2025/v18i5650
Published: 2025-04-22
Container: Asian Journal of Research in Computer Science
Publisher: Sciencedomain International
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.9734/ajrcos/2025/v18i5650,
  title = {Estimating Nutritional Composition from Food Volume Via Deep Learning-Based Depth and Segmentation Models},
  author = {Anh Le and Anh Do and Thanh Nguyen and Binh Nguyen and An Tran and Nha Tran},
  year = {2025},
  journal = {Asian Journal of Research in Computer Science},
  doi = {10.9734/ajrcos/2025/v18i5650},
  url = {https://doi.org/10.9734/ajrcos/2025/v18i5650}
}

RIS

TY  - JOUR
TI  - Estimating Nutritional Composition from Food Volume Via Deep Learning-Based Depth and Segmentation Models
AU  - Anh Le
AU  - Anh Do
AU  - Thanh Nguyen
AU  - Binh Nguyen
AU  - An Tran
AU  - Nha Tran
PY  - 2025
JO  - Asian Journal of Research in Computer Science
DO  - 10.9734/ajrcos/2025/v18i5650
UR  - https://doi.org/10.9734/ajrcos/2025/v18i5650
ER  -

APA

Le, A., Do, A., Nguyen, T., Nguyen, B., Tran, A., & Tran, N. (2025). Estimating Nutritional Composition from Food Volume Via Deep Learning-Based Depth and Segmentation Models. Asian Journal of Research in Computer Science. https://doi.org/10.9734/ajrcos/2025/v18i5650

Source records

crossref · retrieved 2026-09-26T23:09:34.970Z