File size: 1,616 Bytes
efb0321
 
 
 
e20566d
 
 
 
efb0321
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
---
license: other
license_name: aplux-model-farm-license
license_link: https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf
pipeline_tag: image-classification
tags:
- AIoT
- QNN
---

![](https://aiot.aidlux.com/_next/image?url=%2Fapi%2Fv1%2Ffiles%2Fmodel%2Fcover%2F%25E5%259B%25BE-20.png&w=640&q=75)

## ResNet-50: Image Classification

ResNet-50 is a deep convolutional neural network model initially proposed by Microsoft Research to address the degradation problem in training deep networks. It uses "residual learning" by introducing skip connections or "shortcut connections" to avoid vanishing gradient issues, allowing for a significant increase in network depth. ResNet-50 consists of 50 layers, including multiple residual blocks, each containing several convolutional layers. Due to its efficiency and accuracy, ResNet-50 is widely used in image classification, object detection, and other computer vision tasks.

### Source model

- Input shape: 224x224
- Number of parameters: 24.37M
- Model size: 97.4MB
- Output shape: 1x1000

Source model repository: [resnet](https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py)

## Performance Reference

Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models)

## Inference & Model Conversion

Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models)

## License

- Source Model: [BSD-3-CLAUSE](https://github.com/pytorch/vision/blob/main/LICENSE)

- Deployable Model: [APLUX-MODEL-FARM-LICENSE](https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf)