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White-Boxed Artificial Intelligence (WAI) Project Home
Previous projects aimed to provide efficient likelihood free inference, cognitive modelling and user knowledge elicitation.
Problem: Scientific modelling is a key methodology for understanding the world, yet its potential is being held back by both of the necessary steps being difficult for humans: Techniques are lacking for fitting simulator-based models, which most fields use, to data.
Main objective: The main objective of WAI is principles and methods for novel interactive AI that increases the capacity of domain experts to acquire accurate and understandable (“white-box,” in contrast to black-box machine learning) models based on data.
In short, we develop a novel type of interactive AI that interactively learns a white-box model of the expert, in order to then improve her ability to construct and understand models that combine her prior knowledge and what can be learned from data.
(M2) Computational rationality -based cognitive simulators will be developed for the user models, for interacting with visualisations of the models and data, and (M3) interactive modelling will be formulated as experimental design, where an experiment is an interaction with the user through visualisations.
Autumn 2019 – Helsinki Institute for Information Technology | HIIT
Date: November 18, 2019 Abstract: Utilization of unmanned aerial vehicles, drones, has increased explosively during the past couple of years.
Integrating analytics and actuation either utilizing individual drones, drone teams or drone swarms will enable robotization of various environmental operations in the future.
This presentation deals with remote sensing sensor, data calibration and machine learning and presents selected case studies in forest inventory, tree health analysis and grass quality and quantity assessment.
The DroneFinland-team led by Dr Honkavaara has developed several generations of high-performance drone remote sensing systems with cameras, hyperspectral sensors, analytics applications as well as inhouse data processing chains.
- On 27. februar 2021
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