# Logo Detection Using You Only Look Once (YOLO) Method
> Rezkiani K.

URL kanonis: https://discover.unhas.ac.id/publications/pub_scopus_85147332974
Jurnal / Konferensi: Proceedings 2022 2nd International Conference on Electronic and Electrical Engineering and Intelligent System Ice3is 2022
Tahun terbit: 2022
DOI: https://doi.org/10.1109/ICE3IS56585.2022.10010121
Citations: 6

## Authors
- Rezkiani K.

## Abstract
The growing amount of documents necessitates automatic document classification since manual classification takes longer. Logos allow for defining the source of a document rapidly and accurately. Logos are part of the identity attached to companies, organizations, institutions, and individuals. The placement of the logo on each document varies, as does the image quality of a document. This research aimed to identify the logo on a document in the form of a college diploma. This study utilized diplomas from fifteen universities. This system utilizes the You Only Look Once algorithm version 4 (YOLOv4) by implementing the Darknet Framework. The ultimate YOLOv4 model's results indicated that the system could detect and recognize logos with a mean Average Precision (mAP) of 93.73%.

## Keywords
- Logo (programming language)
- Logos Bible Software
- Computer science
- Identity (music)
- Artificial intelligence
- Quality (philosophy)
- Information retrieval
- Image (mathematics)
- Programming language
- Epistemology
- Philosophy
- Acoustics
- Physics
- Operating system

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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