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What is 3D Food Printing Defect Detection Model about?

Deep learning is generally used to perform remote monitoring of three dimensional (3D) printing results, including extrusion-based 3D food printing. One of the widely used deep learning algorithms for defect detection in 3D printing is the convolutional neural network (CNN). However, the process requires high computational costs and a large dataset. This research proposes the Con4ViT model, a hybrid model that combines the strengths of vision transformer with the inherent feature extraction capabilities of

Author

IAES IJAI

Language

EN