TFE SVM
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
- Centre de Recherche en Automatique de Nancy (CRAN),CENPARMI
- Organisation type
- Academia,Academia
- Country
- France, Canada
- Published
- 2 February 2006
- Authors
- Fabian Lauer, Ching Y Suen, Gerard Bloch
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Digit recognition
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
- 600,000 tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- SOTA improvement
- Record confidence
- Unknown
- Citations
- 365
best at affine-transformed digits in table 4
Sources
Where this record came from and when it was last checked.
- Reference
- A trainable feature extractor for handwritten digit recognition
- Last updated
- 28 November 2025
What the numbers mean
What this model is
TFE SVM was published by Centre de Recherche en Automatique de Nancy (CRAN),CENPARMI, in the country recorded as France, during February 2006. The publishing organisation is categorised as academia,Academia.
It works in the domain of Vision, and is recorded as performing the task of digit recognition.
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
Training consumed a corpus of around 600,000 tokens of text.
The reason it appears in this catalogue at all: sOTA improvement.
Answers
TFE SVM — common questions
TFE SVM— who created it?
It was published by Centre de Recherche en Automatique de Nancy (CRAN),CENPARMI, based in France, an organisation categorised as academia,Academia.
TFE SVM— when was it released?
It was published in February 2006. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
TFE SVM— what is it used for?
It works in the domain of Vision, and is recorded as handling the task of digit recognition. 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.
TFE SVM— what GPU do I need to run it?
None. This 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.
TFE SVM— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
TFE SVM— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
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.