Scholarlink

The primary aim of this work is to classify dry grapes using Machine Learning techniques. The model attempts at classifying two raisin types which is highly famous and used in Turkey namely Kecimen and Besni. This classification is done using various features such as perimeter of the raisin, its major and minor axis, the area of the raisin followed by eccentricity and various other geometrical characteristics. Classifiers like SVM, KNN, Naïve Bayes and Decision tree are being used wherein they have achieved 92, 82.4, 86.6 and 85.6%, respectively. It was observed that SVM yielded the highest accuracy after appropriate, training, testing and cross validation was done.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Turkish Raisin Classification Through Deep Learning Prediction Models

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Sindhu P. Menon,
  • Pramodkumar Naik,
  • Basavaraj N. Hiremath,
  • D. Shivamma,
  • George Fernandez

摘要

The primary aim of this work is to classify dry grapes using Machine Learning techniques. The model attempts at classifying two raisin types which is highly famous and used in Turkey namely Kecimen and Besni. This classification is done using various features such as perimeter of the raisin, its major and minor axis, the area of the raisin followed by eccentricity and various other geometrical characteristics. Classifiers like SVM, KNN, Naïve Bayes and Decision tree are being used wherein they have achieved 92, 82.4, 86.6 and 85.6%, respectively. It was observed that SVM yielded the highest accuracy after appropriate, training, testing and cross validation was done.