- What is meant by translational invariance?
- What is translation invariance in AI?
- How do we achieve translation invariance?
- Where is translation invariance used?
What is meant by translational invariance?
Translational invariance implies that, at least in one direction, the object is infinite: for any given point p, the set of points with the same properties due to the translational symmetry form the infinite discrete set p + na | n ∈ Z = p + Z a.
What is translation invariance in AI?
Translation invariance means that the system produces exactly the same response, regardless of how its input is shifted. For example, a face-detector might report "FACE FOUND" for all three images in the top row.
How do we achieve translation invariance?
Also, translational invariance can be achieved by applying a pooling operation, meaning that a region or object can become invariant to (small) translations after the application of pooling. Translational invariance is a highly desirable property in many tasks such as object recognition and audio recognition.
Where is translation invariance used?
As we replace the output with the max in case of max-pooling, hence even if we change the input slightly, it won't affect the values of most of the pooled outputs. Translational Invariance is a useful property where the exact location of the object is not required.