An Edge Detection Approach For Conscious Machines

Yousef, Ahmad; Bakr, Mohamed; Shirani, Shahram; Milliken, Bruce

doi:10.1109/iemcon.2018.8615003

2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) 2018

DOI: 10.1109/iemcon.2018.8615003

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An Edge Detection Approach For Conscious Machines

Ahmad Yousef¹,

Mohamed Bakr²,

Shahram Shirani³

et al.

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2021

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“…However, the method highly relies on the selection of the gray threshold, binarization threshold and geometry threshold. Yousef et al [109] employed edge detection in conscious machine building. The framework is a bio-inspired model, which utilizes a linear summation of the decisions made by previous kernels.…”

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Human Face Detection Techniques: A Comprehensive Review and Future Research Directions

et al. 2021

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Face detection, which is an effortless task for humans, is complex to perform on machines. The recent veer proliferation of computational resources is paving the way for frantic advancement of face detection technology. Many astutely developed algorithms have been proposed to detect faces. However, there is little attention paid in making a comprehensive survey of the available algorithms. This paper aims at providing fourfold discussions on face detection algorithms. First, we explore a wide variety of the available face detection algorithms in five steps, including history, working procedure, advantages, limitations, and use in other fields alongside face detection. Secondly, we include a comparative evaluation among different algorithms in each single method. Thirdly, we provide detailed comparisons among the algorithms epitomized to have an all-inclusive outlook. Lastly, we conclude this study with several promising research directions to pursue. Earlier survey papers on face detection algorithms are limited to just technical details and popularly used algorithms. In our study, however, we cover detailed technical explanations of face detection algorithms and various recent sub-branches of the neural network. We present detailed comparisons among the algorithms in all-inclusive and under sub-branches. We provide the strengths and limitations of these algorithms and a novel literature survey that includes their use besides face detection.

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Human Face Detection Techniques: A Comprehensive Review and Future Research Directions

et al. 2021

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An Edge Detection Approach For Conscious Machines

Cited by 1 publication

References 5 publications

Human Face Detection Techniques: A Comprehensive Review and Future Research Directions

Human Face Detection Techniques: A Comprehensive Review and Future Research Directions

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