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ShrimpFusionNet for Real-Time Shrimp Disease Detection Using Trust-Aware Multimodal Fusion

MMSD25 is a real-world multimodal shrimp disease dataset introduced in this paper. This repository provides a public sanitized reference subset of MMSD25 together with the benchmark protocol to support reproducibility and further research.

1. Dataset Overview

MMSD25 is designed for shrimp disease detection under real aquaculture conditions, where data are noisy, heterogeneous, asynchronous, and partially missing.

The dataset integrates three modalities:

RGB shrimp images captured directly in ponds
Farmer-written textual reports describing shrimp health and pond observations
Environmental sensor streams, including:
- Temperature
- pH
- Dissolved oxygen
- Turbidity
- Salinity

Data were collected from 8 shrimp ponds in the Mekong Delta, Vietnam, under diverse environmental and operational conditions.

2. Public Release Scope

What is publicly released

This repository and the associated Hugging Face page provide:

A sanitized reference subset of MMSD25
The full benchmark protocol, including:
- Data preprocessing procedures The public subset is intended to demonstrate data structure.

What is NOT publicly released

The full MMSD25 dataset is NOT publicly available
Full raw data are restricted due to data governance and farm partner agreements

Access to the full dataset may be considered for non-commercial academic research only, subject to a controlled-access agreement.

3. Dataset Composition (Full Dataset Description)

The full MMSD25 dataset (described in the paper) consists of:

3, 625 RGB shrimp images
12,404 farmer-generated text descriptions
Synchronized multi-channel sensor time series
5 disease classes:
- Healthy
- WSSV
- AHPND
- EHP
- Bacterial necrosis Each sample is verified by aquaculture experts, with inter-annotator agreement reaching Cohen’s κ = 0.86.

4. Train / Validation / Test Split

The benchmark uses a region-based (pond-level) split to evaluate generalization:

Training set: 70% of ponds
Validation set: 10% of ponds
Test set: 20% of ponds (unseen ponds)

This setup supports zero-shot domain evaluation under real deployment conditions.

5. Hugging Face Repository

The public reference subset is hosted on Hugging Face:

https://huggingface.co/ducdatit2002/ShrimpFusionNet

6. Intended Use

MMSD25 is intended for research on:

Multimodal learning (image + text + sensor)
Trust-aware and uncertainty-aware fusion
Robust learning under noisy and missing modalities
Edge AI and IoT-based aquaculture systems

The dataset is not intended for commercial use.

7. Limitations

The public subset is not statistically representative of the full dataset
Some environmental and operational variability present in the full dataset is not exposed
Results obtained on the public subset should not be interpreted as full benchmark performance

8. Citation

If you use MMSD25 or the benchmark protocol, please cite:

@article{shrimpfusionnet2025,
  title={ShrimpFusionNet for Real-Time Shrimp Disease Detection Using Trust-Aware Multimodal Fusion},
  author={Le, Tan Duy and Huynh, Kha Tu and Pham, Duc Dat and Nguyen, Hong Quan and Nguyen, Minh Tu},
  year={2025}
}

9. License

The public subset of MMSD25 is released for non-commercial research use only.

11. Contact

For questions or controlled access requests to the full dataset:

Duc Dat Pham
Email: ducdatit2002@gmail.com

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