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What is 3D Fruit Classification Using ConvNet about?

This document discusses using a convolutional neural network (ConvNet) to classify 3D fruit objects from multiple images. The goal is to achieve better accuracy in recognizing fruits like apples and bananas by capturing images from different angles and feeding them into a ConvNet model for classification. The ConvNet architecture is used to classify 3D fruit objects from multiple images with the aim of improving accuracy over other methods.

Author

Achmad Lukman

Language

EN