ResNet
Definition
ResNet uses residual connections for better trainability of deep networks.
A family of deep neural networks that uses residual blocks with skip connections to make very deep models more trainable.
Simply explained
Shortcuts between computation blocks help a very deep model to pass on its information.
Why it matters in practice
The term helps to select, develop, evaluate AI systems in a well-founded manner and realistically assess their technical risks.
Example from business
A ResNet classifies quality images in a production inspection.
Limits and pitfalls
- Viewing ResNet as a single immutable model or deriving better generalization solely from depth.
Origin & history
He, Zhang, Ren, and Sun published ResNet in 2015.
Use in mid-sized companies
- Possible example: A ResNet classifies quality images in a production inspection.
Frequently asked questions
What does ResNet mean?
A family of deep neural networks that uses residual blocks with skip connections to make very deep models more trainable. What mistakes should be avoided? Viewing ResNet as a single immutable model or deriving better generalization solely from depth.
Sources
Source checked on 10.10.2026. Editorial application examples are hypothetical; no proof of real customer results.
Editorially reviewed on: