M

Miewid Msv2

Developed by conservationxlabs
MiewID-msv2 is a wildlife individual re-identification feature extractor trained through contrastive learning, supporting the recognition of 54 terrestrial and aquatic species.
Downloads 135
Release Time : 7/2/2024

Model Overview

This model serves as a feature backbone network for wildlife individual re-identification (re-ID), trained on large-scale high-quality datasets, capable of extracting feature vectors usable for cross-species individual matching and species classification.

Model Features

Multi-species Support
Supports individual identification of 54 terrestrial and aquatic species, including fin, tail, side, and facial features.
High-performance Feature Extraction
Demonstrates strong generalization across multiple species, achieving over 90% mAP for species like Amur tigers and bottlenose dolphins.
Large-scale Training Data
Integrates high-quality training data from the Wildbook platform, Happywhale competition datasets, and multiple public datasets.

Model Capabilities

Wildlife individual identification
Cross-species feature matching
Species classification
Image feature extraction

Use Cases

Wildlife Conservation
Amur Tiger Individual Tracking
Individual identification and tracking through tiger side features
Achieves 91.8 mAP and 100% Rank-1 accuracy on test sets
Marine Mammal Research
Individual identification of marine animals like beluga whales and bottlenose dolphins
Bottlenose dolphin recognition reaches 85.69 mAP and 93.99% Rank-1 accuracy
Ecological Research
Population Estimation
Estimating wildlife population sizes through individual identification technology
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
© 2025AIbase