ISR network
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
- Stanford University
- Organisation type
- Academia
- Country
- United States of America
- Published
- 1 October 1990
- Authors
- James Keeler, David Rumelhart, Wee Leow
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Character recognition (OCR)
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
“We used a training and test set of about 9,000 and 1,800 characters respectively. “
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
- Historical significance
- Record confidence
- Confident
Sources
Where this record came from and when it was last checked.
- Reference
- Integrated Segmentation and Recognition of Hand-Printed Numerals
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
ISR network was published by Stanford University, in the country recorded as United States of America, during October 1990. The category the publisher falls under is academia.
It works in the domain of Vision, and is recorded as performing the task of character recognition (OCR).
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Training and provenance
Training consumed a corpus of around 600,000 tokens of text.
The reason it appears in this catalogue at all: historical significance.
Answers
ISR network — common questions
ISR network— when was it released?
It was published in October 1990. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
ISR network— what is it used for?
It works in the domain of Vision, and is recorded as handling the task of character recognition (OCR). Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
ISR network— 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.
ISR network— 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.
ISR network— 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.
ISR network— who created it?
It was published by Stanford University, based in United States of America, an organisation categorised as academia.
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.