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Table 1 Overview of five backbone models

From: Transfer learning for medical image classification: a literature review

Model type

Model

Released year

Parameters (all)

Parameters (FE only)

Trainable layers (FE + FC layers)

Dataset

Shallow and linear

LeNet5

1998

60,000

1,716

4 (2 + 2)

MNIST

AlexNet

2012

62.3 M

3.7 M

8 (5 + 3)

ImageNet

VGG16

2014

134.2 M

14.7 M

16 (13 + 3)

Deep

GoogLeNet

2014

5.3 M

5.3 M

22 (21 + 1)

ResNet50

2015

25.6 M

23.5 M

51 (50 + 1)

  1. FE: feature extraction, FC: fully connected layers; MNIST database: Modified National Institute of Standards and Technology database of handwritten digits with 60,000 training and 10,000 test images, ImageNet database: organized according to the WordNet hierarchy with over 14 million hand-annotated images for visual object recognition research