A Face Detection System: A Comprehensive Survey

Faqeda Hassen; Mohammed Abdullah Naser

doi:10.29196/jubpas.v32i2.5266

Article Details

A Face Detection System: A Comprehensive Survey

Authors:

Faqeda Hassen | Mohammed Abdullah Naser

Publisher:

University of Babylon

Journal:

JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.32 Issue 2, pp.45-61

Document Type:

Article

Publication Date:

1/2024

Document Language:

English

Document ID (Org No.):

2001383207

pISSN:

2312-8135

DOI:

10.29196/jubpas.v32i2.5266

Keywords:

Abstract:

 The domain of facial detection has witnessed significant advancement, mostly attributed to the progress in machine learning and deep learning methodologies. These enhancements have resulted in a fundamental change in the field. Face detection algorithms are extensively utilized in several domains, such as security, surveillance, and social networking applications. This survey has thoroughly investigated various methodologies for facial identification, with a focus on the challenges, applications, and evolution from traditional to deep learning-based approaches. Furthermore, it provides important insights into commonly used datasets for facial detection, including a comprehensive examination of their unique characteristics. The study is structured sequentially, commencing with an introduction to the assessment of significant previous research and the challenges faced by face detection algorithms. Subsequently, the investigation delves into different practical uses, delineates methods for identifying, and scrutinizes frequently employed data sets. The transition from traditional classifiers to deep learning models in face identification technology represents a significant improvement in addressing the complexities of face detection in various environments. Despite the obstacles that now exist, the continuous advancements in deep learning offer promising solutions that enhance the accuracy and efficiency of face identification systems in a wide range of applications.

Article Details

A Face Detection System: A Comprehensive Survey

Authors:

Faqeda Hassen | Mohammed Abdullah Naser

Publisher:

University of Babylon

Journal:

JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.32 Issue 2, pp.45-61

Document Type:

Article

Publication Date:

1/2024

Document Language:

English

Document ID (Org No.):

2001383207

pISSN:

2312-8135

DOI:

10.29196/jubpas.v32i2.5266

face detection

machine learning

deep learning

spatial domain and CNN

Issues

Article Details

A Face Detection System: A Comprehensive Survey

Authors: Faqeda Hassen | Mohammed Abdullah Naser

Publisher: University of Babylon

Journal: JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.32 Issue 2, pp.45-61

Document Type: Article

Publication Date: 1/2024

Document Language: English

Document ID (Org No.): 2001383207

pISSN: 2312-8135

DOI: 10.29196/jubpas.v32i2.5266

face detection

machine learning

deep learning

spatial domain and CNN

Issues

Authors:

Faqeda Hassen | Mohammed Abdullah Naser

Publisher:

University of Babylon

Journal:

JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.32 Issue 2, pp.45-61

Document Type:

Article

Publication Date:

1/2024

Document Language:

English

Document ID (Org No.):

2001383207

pISSN:

2312-8135

DOI:

10.29196/jubpas.v32i2.5266