The Use of a DenseNet201 CNN and Other Deep Learning Techniques for Exploratory Data Analysis of Red Wine Quality-Reference-Cited by-同舟云学术

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The Use of a DenseNet201 CNN and Other Deep Learning Techniques for Exploratory Data Analysis of Red Wine Quality

Published:2024-05-24 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 5th International Conference for Emerging Technology (INCET)
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Author:

Pritam Nishant¹,Gill Kanwarpartap Singh¹,Kumar Mukesh²,Rawat Ruchira³

Affiliation:

1. Chitkara University Institute of Engineering and Technology, Chitkara University,Punjab,India

2. Computer Science & Engineering, Graphic Era Hill University,Dehradun,Uttarakhand,India,248002

3. Computer Science & Engineering, Graphic Era Deemed to be University,Dehradun,Uttarakhand,India,248002

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592862/10592849/10593018.pdf?arnumber=10593018

Reference20 articles.

1. Enhancing red wine quality prediction through Machine Learning approaches with Hyperparameters optimization technique

2. Energy efficient fault tolerance techniques in green cloud computing: A systematic survey and taxonomy

3. Machine learning-based predictive modelling for the enhancement of wine quality

4. Cattle health monitoring system using wireless sensor network: a survey from innovation perspective

5. Wine Quality Prediction Using Machine Learning Techniques

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