Multiple Classification of Flower Images Using Transfer Learning

Deep learning technologies have been successful in many fields in recent years. Image classification problem is one of the areas where the use of the results is successful. The study draws attention to the use of pretrained models in problem solving. With the approach called transfer learning, frequently used pretrained deep learning models such as Alexnet, Googlenet, VGG16, DenseNet and ResNet are used for image classification. The results show that the models used achieve acceptable performance rates while the highest performance is achieved with the VGG16 model.

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Multiple Classification of Flower Images Using Transfer Learning

Semantic Scholar · Computer Science · 2019

Abstract

Deep learning technologies have been successful in many fields in recent years. Image classification problem is one of the areas where the use of the results is successful. The study draws attention to the use of pretrained models in problem solving. With the approach called transfer learning, frequently used pretrained deep learning models such as Alexnet, Googlenet, VGG16, DenseNet and ResNet are used for image classification. The results show that the models used achieve acceptable performance rates while the highest performance is achieved with the VGG16 model.

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