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Title:Creating a Dataset and Models Based on Convolutional Neural Networks to Improve Fruit Classification
Conference:SYNASC2021
Tags:Alexnets, convolutional neural networks, fruits dataset and model training pipelines
Abstract:
We are often curious to find out what fruit is found in a tree when we are walking through parks or a botanical garden. Fruit classification is a complex activity that depends on the datasets used and the deep learning methods applied to them. This paper aims to present the steps by which we created a dataset with 262 fruits, and then how we created several models based on it. Evaluation and testing have shown us that the resource and models created can be useful to those who want to create applications that recognize fruits.
Creating a Dataset and Models Based on Convolutional Neural Networks to Improve Fruit Classification
Creating a Dataset and Models Based on Convolutional Neural Networks to Improve Fruit Classification
