SVM for face detection
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Massachusetts Institute of Technology (MIT)
- Organisation type
- Academia
- Country
- United States of America
- Published
- 17 June 1997
- Authors
- E. Osuna, R. Freund, F. Girosi
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Object detection
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- 50,000 tokens
Section 1: "The problem that we have to solve involves training a classifier to discriminate between face and non-face patterns, using a data set of 50,000points. "
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Citations
- 3,851
Sources
Where this record came from and when it was last checked.
- Reference
- Training Support Vector Machines: An Application to Face Detection
- Last updated
- 28 November 2025
What the numbers mean
What this model is
SVM for face detection was published by Massachusetts Institute of Technology (MIT), in United States of America, in June 1997. academia is the category the publisher falls under.
It works in Vision, and is recorded as doing object detection.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
What went into building it
The training set ran to roughly 50,000 tokens.
Answers
SVM for face detection — common questions
What GPU do I need to run SVM for face detection?
None. SVM for face detection is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is SVM for face detection open source?
The licensing for SVM for face detection was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does SVM for face detection have?
No parameter count has been published for SVM for face detection, which is why no memory or speed figure appears on this page.
Who created SVM for face detection?
SVM for face detection was published by Massachusetts Institute of Technology (MIT), based in United States of America, categorised as academia.
When was SVM for face detection released?
SVM for face detection was published in June 1997. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is SVM for face detection used for?
SVM for face detection works in Vision, and is recorded as handling object detection. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.