Deep learning is driving recent advances behind many everyday technologies, including
speech and image recognition, natural language processing and autonomous driving. It is …

Artificial intelligence (AI) is poised to revolutionize many aspects of science, including the
study of evolutionary morphology. While classical AI methods such as principal component …

Although turtles play a key role in maintaining healthy and balanced environments, these
are endangered due to global trade to meet the high demand for food, medicine, and pets in …

Numerous studies have proven the potential of deep learning models for classifying wildlife.
Such models can reduce the workload of experts by automating species classification to …

Most machine learning methods for animal recognition in camera trap images are limited to
mammal identification and group birds into a single class. Machine learning methods for …

Sea turtles exhibit high migratory rates and occupy a broad range of habitats, which in turn
makes monitoring these taxa challenging. Applying deep learning (DL) models to vast …

Biodiversity image repositories are crucial sources for training machine learning approaches
to support biological research. Metadata about object (eg image) quality is a putatively …

Flexible metadata pipelines are crucial for supporting the FAIR data principles. Despite this
need, researchers seldom report their approaches for identifying metadata standards and …

Artificial intelligence (AI) is poised to revolutionize many aspects of science, including the
study of evolutionary morphology. While classical AI methods such as principal component …