Table 1.
Overview of five backbone models
| 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) |
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