Deployment involves using the results of your analysis to perform predictive analysis, launch a machine learning program, or continue to provide insights to decision-makers in your company or organization using data analysis tools that were a result of your study.
An evaluation of the responsibility of generative AI models presents unique challenges that require holistic and practical solutions. This paper introduces an enhanced version of the VERIFAI framework, which extends beyond classification models to assess generative language models as well… Read More »Towards Responsibility Evaluation of Generative Language Models
Ziel dieser Arbeit ist die Entwicklung und Validierung eines automatisierten Prognosemodells für Gepäckmengen am Hamburger Flughafen unter Verwendung der Low-Code AutoML-Bibliothek PyCaret. Durch die Automatisierung signifikanter Phasen des Machine-Learning-Lebenszyklus konnten präzise Vorhersagen für Gepäckstücke pro Flug innerhalb und außerhalb der… Read More »Automatisierte prädiktive Analytik in der Gepäckabfertigung
Our research endeavors to advance the concept of responsible artificial intelligence (AI), a topic of increasing importance within EU policy discussions. The EU has recently issued several publications emphasizing the necessity of trust in AI, underscoring the dual nature of… Read More »Responsible Artificial Intelligence: A Structured Literature Review
The growing integration of artificial intelligence (AI) in diverse sectors underscores the need for comprehensive and standardized approaches to ensure AI responsibility. However, the absence of a holistic framework to evaluate the fairness, privacy-preserving, secure, explainable, and human-centered facets of… Read More »Bridging the Gap between Theory and Practice: Towards Responsible AI Evaluation
This work represents the first step towards a unified framework for evaluating an AI system’s responsibility by building a prototype application.The python based web-application uses several libraries for testing the fairness, robustness, privacy, and explainability of a machine-learning model as… Read More »VERIFAI – A Step Towards Evaluating the Responsibility of AI-Systems
This paper implements a ROS package for segmenting Point Clouds using Gradual Point Cloud Processing (GPCP). The implementation is integrated with RTAB-Map to produce a segmented point cloud of the environment. The RGB-D SLAM Dataset was used to validate the… Read More »Point Cloud Segmentation using Projection: A ROS Implementation