Damir D. Torrico

University of Melbourne

论文数

7

总引用数

520

H-Index

7

关于

暂无简介。

研究焦点

Computer science7 · 520 次引用
Artificial intelligence7 · 520 次引用
Machine learning6 · 458 次引用
Mathematics5 · 366 次引用
Mouthfeel4 · 277 次引用
Quality (philosophy)3 · 220 次引用
Chemistry3 · 204 次引用
Psychology3 · 181 次引用
Biometrics2 · 158 次引用
Statistics2 · 158 次引用
Algorithm2 · 151 次引用
Principal component analysis2 · 151 次引用

主要成就

7
H 指数
7
论文
520
总引用数
74
篇均引用
🏆 最高被引论文
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 次引用 · 2019
📈 最高产年份: 2019 (3 论文)
🤝 主要合作者: 7
🏛 所属机构: University of Melbourne

代表论文

  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 次引用 · 2019
  2. 2
    Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages
    92 次引用 · 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 次引用 · 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 次引用 · 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 次引用 · 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 次引用 · 2016
  7. 7
    Assessment of Beer Quality Based on a Robotic Pourer, Computer Vision, and Machine Learning Algorithms Using Commercial Beers
    53 次引用 · 2018

主要合作者

CGClaudia Gonzalez Viejo7 篇合著论文SFSigfredo Fuentes7 篇合著论文FRFrank R. Dunshea6 篇合著论文KHKate Howell3 篇合著论文GLGuangjun Li1 篇合著论文BCBruna Condé1 篇合著论文RDR. D. COLLMANN1 篇合著论文
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