Evaluation of AI solutions performance based on testing datasets
Laboratoire National de Métrologie et d’Essais - LNE
Location
Remote
Arable farming
Food processing
Greenhouse
Horticulture
Livestock farming
Tree Crops
Viticulture
By having your AI system tested by the LNE, you ensure it meets the highest standards of safety and performance, boosting your product’s reliability and trustworthiness in the market. Partnering with the LNE for rigorous testing of your AI technologies gives you a competitive edge, as their certification enhances credibility and opens doors to new market opportunities both locally and globally. LNE's AI performance evaluation service uses comprehensive testing datasets to assess the accuracy, robustness, and efficiency of your AI systems by comparing the outputs of the system with a dataset of reference values. By testing real-world scenarios, LNE ensures that your AI models meet industry standards and regulatory requirements, helping you improve performance, reliability, and market readiness. LNE utilises a diverse range of carefully curated datasets that simulate various operating conditions and environments in which the AI may be deployed. These datasets allow for in-depth testing of the system’s ability to process information, make decisions, and produce accurate outputs. The service covers a broad spectrum of AI applications, from machine learning models and deep learning algorithms to computer vision systems, natural language processing (NLP), and autonomous robotics. The evaluation process examines key performance metrics such as accuracy, precision, recall, response time and scalability. It also identifies any potential biases in the system, ensuring that the AI behaves fairly and ethically across different user groups or environmental variables.
Collection of test data
Performance evaluation
Test design
Test execution
Test setup
