Taxonomic Classification

Taxonomic classification, the science of organizing and naming organisms, is undergoing a transformation driven by advancements in machine learning. Current research focuses on improving the accuracy and efficiency of classification using multimodal approaches that integrate image data, genetic information (like DNA barcodes), and textual descriptions, often employing deep learning architectures such as convolutional neural networks, transformers, and contrastive learning models. These improvements are crucial for large-scale biodiversity monitoring, enabling more efficient and accurate species identification, and facilitating advancements in fields ranging from environmental science to medical research. Furthermore, research is exploring how to leverage taxonomic hierarchies within machine learning models to improve performance and address challenges like imbalanced datasets and the detection of unknown species.