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October 12, 2025Open Access

Detection of trade in products derived from threatened species using machine learning and a smartphone

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Authors

RKRitwik KulkarniWHWU Han-qinEMEnrico Di Minin

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Overview

Machine learning identifies wildlife products in images, suggesting effective prevention of illegal trade.

Key Points

  • The method accurately detects wildlife products, identifying items like ivory with an accuracy of 91.3%.
  • Using image data from elephants, pangolins, and tigers, the best model achieved 84.2% overall accuracy.
  • Trained models allow for real-time identification of threatened species' products during wildlife trade monitoring.
  • A smartphone application was developed to facilitate easy access for law enforcement and regulatory agencies.

Cite This Study

Kulkarni et al. (2025) studied this question.

synapsesocial.com/papers/68ec1be02b8fa9b2b78ad118https://doi.org/10.48550/arxiv.2509.06585
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Wildlife Product Trading in Online Social Networks: A Case Study on Ivory-Related Product Sales Promotion Posts2024
  2. 2A multimodal learning approach for automated detection of wildlife trade on social media2026 · 1 citations
  3. 3Detect and Trace: An Australian Field Trial Using Machine-Learning Tools to Combat Illegal Wildlife Trade2026
  4. 4Developing a simple automatic elephant detection system aimed at achieving individual recognition in a specific forest site using image processing and supervised machine learning2026
  5. 5Research on Prediction of Illegal Wildlife Trade Based on PCA and Multiple Linear Regression2024