# Real Time Object Detection System with YOLO and CNN Models: A Review

arXiv: https://arxiv.org/abs/2208.00773 · HTML: https://mlsanity.com/paper/2208.00773/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 20 references that are in the map.
- First posted on arXiv 23 Jul 2022.

## Builds on (most cited first, 2 of 2)

- [You Only Look Once: Unified, Real-Time Object Detection](https://mlsanity.com/paper/1506.02640/) (2015)
- [Internet of Things(IoT) Based Multilevel Drunken Driving Detection and Prevention System Using Raspberry Pi 3](https://mlsanity.com/paper/2004.10174/) (2020)

## Built on by (most cited first, 4 of 4)

- [Brain Cancer Segmentation Using YOLOv5 Deep Neural Network](https://mlsanity.com/paper/2212.13599/) (2022)
- [AI driven shadow model detection in agropv farms](https://mlsanity.com/paper/2304.07853/) (2023)
- [A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges](https://mlsanity.com/paper/2310.16360/) (2023)
- [Enhanced Drift-Aware Computer Vision Architecture for Autonomous Driving](https://mlsanity.com/paper/2508.17975/) (2025)

## Abstract (arXiv)

The field of artificial intelligence is built on object detection techniques. YOU ONLY LOOK ONCE (YOLO) algorithm and it's more evolved versions are briefly described in this research survey. This survey is all about YOLO and convolution neural networks (CNN)in the direction of real time object detection.YOLO does generalized object representation more effectively without precision losses than other object detection models.CNN architecture models have the ability to eliminate highlights and identify objects in any given image. When implemented appropriately, CNN models can address issues like deformity diagnosis, creating educational or instructive application, etc. This article reached atnumber of observations and perspective findings through the analysis.Also it provides support for the focused visual information and feature extraction in the financial and other industries, highlights the method of target detection and feature selection, and briefly describe the development process of YOLO algorithm.