Damir D. Torrico

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Research Focus

Key Achievements

Top Papers

1. 1
   Development of Artificial Neural Network Models to Assess Beer Acceptability Based on Sensory Properties Using a Robotic Pourer: A Comparative Model Approach to Achieve an Artificial Intelligence System

   96 citations · 2019
2. 2
   Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages

   92 citations · 2019
3. 3
   Assessment of beer quality based on foamability and chemical composition using computer vision algorithms, near infrared spectroscopy and machine learning algorithms

   89 citations · 2017
4. 4
   Robotics and computer vision techniques combined with non-invasive consumer biometrics to assess quality traits from beer foamability using machine learning: A potential for artificial intelligence applications

   66 citations · 2018
5. 5
   Bubbles, Foam Formation, Stability and Consumer Perception of Carbonated Drinks: A Review of Current, New and Emerging Technologies for Rapid Assessment and Control

   62 citations · 2019
6. 6
   Development of a robotic pourer constructed with ubiquitous materials, open hardware and sensors to assess beer foam quality using computer vision and pattern recognition algorithms: RoboBEER

   62 citations · 2016
7. 7
   Assessment of Beer Quality Based on a Robotic Pourer, Computer Vision, and Machine Learning Algorithms Using Commercial Beers

   53 citations · 2018

Key Collaborators