YOLO at Your Fingertips: Object Detection without Coding

Digital Poster/Demo
In session Postersession No. 1 , Sept. 3, 2025, 15:45 – 16:30
Exact timing: 15:45 – 16:30

Image-based data analysis is becoming increasingly important in Earth and environmental sciences – for example, in marine biodiversity monitoring, drone image evaluation, or automated habitat classification. Deep learning approaches such as YOLO (You Only Look Once) offer powerful tools for object detection, but their application is often limited by technical complexity and the need for programming skills.

In this demo, I present a user-friendly graphical interface that allows researchers to upload their own image datasets and annotations, and then configure and run a complete object detection workflow – including data preparation, model training, validation, and testing – all without writing any code. This tool is particularly aimed at scientists working with image data who want to apply deep learning methods without needing expertise in machine learning frameworks.

The demo will showcase typical use cases from marine biology, but the workflow is domain-agnostic and easily transferable to a wide range of Earth and environmental science applications. In the future, the tool will be available via BinderHub, allowing users to run the entire workflow directly in their web browser without any local installation.