Looking Through the Veil: An Autonomous Approach to Remote Assessment

Coping with Obscurity

Perceiving the Unseen

Apollo 13’s reentry sequence. Credit: Safely to Earth

Objective Inference Through Uncertainty

  • Probabilities of hidden state at the start
  • Transition probabilities from one hidden state to another
  • Emission probabilities determine how likely each observation would happen, given the hidden state
HMM inferring the weather based on user activity. Credit: Terencehonles
  • The most likely sequence of hidden states (e.g. sunny, sunny, rain, sunny)
  • The distribution of hidden states currently (e.g. 30% rain, 70% sunny)
  • The distribution of hidden states in a past point

Digital Twinning for Smallholder Farmers

Unveiling the Big Picture

An ecosystem for automated remote sensing and advisory

Resources

  1. Decision Making with Incomplete Information
  2. Hidden Markov Models
  3. Maximum Likelihood Estimation
  4. Expectation Maximisation
  5. Baum-Welch Algorithm
  6. Bayesian Inference

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Darrell Leong, Ph.D.

Darrell Leong, Ph.D.

Decision scientist developing advisory engines across a variety of applications.