Deep-Learning-CNN for Detecting Covered Faces with Niqab

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Alashbi Abdulaziz A.; Sunar Mohd Shahrizal; Alqahtani Zieb

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Journal Paper

Paper Information

Journal: Journal of Information Technology Management Year:2022 | Volume:14 | Issue:supplement 1 Page(s): 114-123

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Title

Deep-Learning-CNN for Detecting Covered Faces with Niqab

Author(s)

Alashbi Abdulaziz A. | Sunar Mohd Shahrizal | Alqahtani Zieb | Issue Writer Certificate

Keywords

Face-detection

Object-detection

Computer Vison

Deep learning

Artificial Intelligence

Convolutional Neural Network

Abstract

Detecting occluded faces is a non-trivial problem for face detection in computer vision. This challenge becomes more difficult when the occlusion covers majority of the face. Despite the high performance of current state-of-the-art face detection algorithms, the detection of occluded and covered faces is an unsolved problem and is still worthy of study. In this paper, a deep-learning-Face-detection model Niqab-Face-Detector is proposed along with context-based labeling technique for detecting unconstrained veiled faces such as faces covered with niqab. An experimental test was conducted to evaluate the performances of the proposed model using the Niqab-Face dataset. The experiment showed encouraging results and improved accuracy compared with state-of-the-art face detection algorithms.

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APA: Copy

Alqahtani, Zieb. (2022). Deep-Learning-CNN for Detecting Covered Faces with Niqab. JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT, 14(supplement 1), 114-123. SID. https://sid.ir/paper/977688/en

Vancouver: Copy

Alqahtani Zieb. Deep-Learning-CNN for Detecting Covered Faces with Niqab. JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT[Internet]. 2022;14(supplement 1):114-123. Available from: https://sid.ir/paper/977688/en

IEEE: Copy

Zieb Alqahtani, “Deep-Learning-CNN for Detecting Covered Faces with Niqab,” JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT, vol. 14, no. supplement 1, pp. 114–123, 2022, [Online]. Available: https://sid.ir/paper/977688/en

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