Computer vision and machine learning systems for identifying or classifying biological species from images, observations, or other data.
Projects may include image preprocessing, classification, object detection, feature learning, metadata integration, and model evaluation.
Applications include field observations, biodiversity monitoring, specimen databases, and ecological research.
Implementation is selected according to the available data, technical constraints, required level of automation, and the existing software or research environment. The solution can be implemented as a standalone component or integrated into a larger system.
The resulting system is intended to provide a clear computational workflow that can be evaluated, maintained, and extended as the project develops. Model choice, data processing, interfaces, and deployment can therefore be adapted to the requirements of the specific project.