# Delegating Custom Object Detection Tasks to a Universal Classification System

Source: [Delegating Custom Object Detection Tasks to a Universal Classification System](<https://www.sota2.com/research/paper/68fa612e1e209131ce9f3085>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T19:54:34.816Z

Authors: Andrew Gleibman

Published: 2013-12-19T08:17:24.000Z

## Abstract

In this paper, a concept of multipurpose object detection system, recently introduced in our previous work, is clarified. The business aspect of this method is transformation of a classifier into an object detector/locator via an image grid. This is a universal framework for locating objects of interest through classification. The framework standardizes and simplifies implementation of custom systems by doing only a custom analysis of the classification results on the image grid.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1401.6126>)

[PDF](<https://arxiv.org/pdf/1401.6126.pdf>)