Sigfredo Fuentes

University of Melbourne

论文数

21

总引用数

888

H-Index

16

关于

暂无简介。

研究焦点

Computer science19 · 776 次引用
Artificial intelligence16 · 727 次引用
Machine learning11 · 633 次引用
Mathematics7 · 484 次引用
Chemistry9 · 392 次引用
Quality (philosophy)10 · 355 次引用
Mouthfeel5 · 307 次引用
Food science8 · 303 次引用
Robot5 · 182 次引用
Psychology3 · 181 次引用
Biometrics3 · 180 次引用
Robotics4 · 179 次引用

主要成就

16
H 指数
21
论文
888
总引用数
42
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: 23
🏛 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
    Artificial Intelligence Applied to a Robotic Dairy Farm to Model Milk Productivity and Quality based on Cow Data and Daily Environmental Parameters
    82 次引用 · 2020
  5. 5
    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
  6. 6
    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
  7. 7
    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
  8. 8
    Assessment of Beer Quality Based on a Robotic Pourer, Computer Vision, and Machine Learning Algorithms Using Commercial Beers
    53 次引用 · 2018
  9. 9
    Low-Cost Methods to Assess Beer Quality Using Artificial Intelligence Involving Robotics, an Electronic Nose, and Machine Learning
    46 次引用 · 2020
  10. 10
    Development of a robotic and computer vision method to assess foam quality in sparkling wines
    41 次引用 · 2016

主要合作者

CGClaudia Gonzalez Viejo16 篇合著论文FRFrank R. Dunshea10 篇合著论文KHKate Howell7 篇合著论文DDDamir D. Torrico7 篇合著论文ETEden Tongson5 篇合著论文BCBruna Condé4 篇合著论文RDR. D. COLLMANN3 篇合著论文MCMaeva Caron3 篇合著论文NLNir Lipovetzky3 篇合著论文HHHai Ho Dac2 篇合著论文SNSonja Needs2 篇合著论文KLKerry L. Wilkinson1 篇合著论文BMBruno Martins Lima1 篇合著论文JAJulie A. Culbert1 篇合著论文SSSurinder S. Chauhan1 篇合著论文CHCarmen Hernández‐Brenes1 篇合著论文DXDi Xiao1 篇合著论文BTBart Tesselaar1 篇合著论文GLGuangjun Li1 篇合著论文DFDanielle Fraser1 篇合著论文
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