# A Review of Object Detection Models based on Convolutional Neural Network

Source: [A Review of Object Detection Models based on Convolutional Neural Network](<https://www.sota2.com/research/paper/68fa67b81e209131cea18195>)

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

Data updated: 2025-10-27T06:02:46.151Z

Authors: F. Sultana, A. Sufian, P. Dutta

Published: 2019-05-05T05:45:21.000Z

## Abstract

Convolutional Neural Network (CNN) has become the state-of-the-art for object detection in image task. In this chapter, we have explained different state-of-the-art CNN based object detection models. We have made this review with categorization those detection models according to two different approaches: two-stage approach and one-stage approach. Through this chapter, it has shown advancements in object detection models from R-CNN to latest RefineDet. It has also discussed the model description and training details of each model. Here, we have also drawn a comparison among those models.

## 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/1905.01614>)

[PDF](<https://arxiv.org/pdf/1905.01614.pdf>)