Active Learning for Biodiversity Monitoring: From Label Efficiency to Reliable Ecological Inference
cs.LG
Submitted: 2026-09-23
Updated: 2026-09-23
Terminology
Sources
- STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional Settings
- Efficient Pipeline for Camera Trap Image Review
- modAL: A modular active learning framework for Python
- Adaptive Diversity-Uncertainty Active Learning with Redundancy Control for Bioacoustic Event Classification
- The Search for Squawk: Agile Modeling in Bioacoustics
- Multimodal Foundation Models for Zero-shot Animal Species Recognition in Camera Trap Images
- Pytorch-Wildlife: A Collaborative Deep Learning Framework for Conservation
- DeepAL: Deep Active Learning in Python
- Finding Needles in the Haystack: Transductive Active Labeling in Ecology
- Aggregation Strategies for Efficient Annotation of Bioacoustic Sound Events Using Active Learning
- Determinantal point process sampling for bioacoustic active learning
- The Accuracy Cost of Weakness: A Theoretical Analysis of Fixed-Segment Weak Labeling for Events in Time
- BioDCASE: Active Learning for Bioacoustics
- Parting with Illusions about Deep Active Learning
- Deep Active Audio Feature Learning in Resource-Constrained Environments
- A model-agnostic active learning approach for animal detection from camera traps
- Can Masked Autoencoders Also Listen to Birds?
- Towards Deep Active Learning in Avian Bioacoustics
- Active Bird2Vec: Towards End-to-End Bird Sound Monitoring with Transformers
- Active Learning for Animal Re-Identification with Ambiguity-Aware Sampling
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