Addressing class imbalance in remote sensing using deep learning approaches: a systematic literature review
S Sharma, A Gosain - Evolutionary Intelligence, 2025 - Springer
Class imbalance is one of the major issues for the application of deep learning for remote
sensing imagery. High-resolution remote sensing image sample sets are prone to cause the …
sensing imagery. High-resolution remote sensing image sample sets are prone to cause the …
Pytorch-Wildlife: A Collaborative Deep Learning Framework for Conservation
The alarming decline in global biodiversity, driven by various factors, underscores the urgent
need for large-scale wildlife monitoring. In response, scientists have turned to automated …
need for large-scale wildlife monitoring. In response, scientists have turned to automated …
Modeling semantic correlation and hierarchy for real-world wildlife recognition
We explore the challenges of human-in-the-loop frameworks to label wildlife recognition
datasets with a neural network. In wildlife imagery, the main challenges for a model to assist …
datasets with a neural network. In wildlife imagery, the main challenges for a model to assist …
New frontiers in AI for biodiversity research and conservation with multimodal language models
The integration of Artificial Intelligence (AI) into biodiversity research and conservation is
growing rapidly, demonstrating great potential in reducing the intensive human labor …
growing rapidly, demonstrating great potential in reducing the intensive human labor …
Multi-modal Language Models in Bioacoustics with Zero-shot Transfer: A Case Study
Automatically detecting sound events with Artificial Intelligence (AI) has become increasingly
popular in the field of bioacoustics, particularly for wildlife monitoring and conservation …
popular in the field of bioacoustics, particularly for wildlife monitoring and conservation …