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MNet: A Framework to Reduce Fruit Image Misclassification
2021
Ingénierie des Systèmes d'Information
Fast and accurate fruit classification is a major problem in the farming business. To achieve the same, the most popular technique used to build a classification model is "Transfer Learning", in which the weights of pretrained models are used in a new model to solve different but related problems. This technique assures the fast model building with a reduction in generalization error. After testing a popular image classification models namely, DenseNet161, InceptionV3, and MobileNetV2 on
doi:10.18280/isi.260203
fatcat:dt6b2jwry5cwdgafc4yqevmble