Md. Shamim Ahsan

Prof. Md. Shamim Ahsan

Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh
orcid

Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 June 2011 in Applied Surface Science
Verified
Journal Article
Closed access
Md. Shamim AhsanMd. Shamim Ahsan
Md. Shamim Ahsan
FAFarid Ahmed
Farid Ahmed
YKYeong Gyu Kim
Yeong Gyu Kim
MLMan Seop Lee
Man Seop Lee
MJMartin Jun
Martin Jun

1 June 2019 in Applied Surface Science
Verified
Journal Article
Closed access
ISIk-Bu Sohn
Ik-Bu Sohn
HCHun-Kook Choi
Hun-Kook Choi
YNYoung-Chul Noh
Young-Chul Noh
JKJongyeol Kim
Jongyeol Kim
Md. Shamim AhsanMd. Shamim Ahsan
Md. Shamim Ahsan

26 September 2021 in Electronics
Verified
Journal Article
Open access
PDF file
Md Khaled HasanMd Khaled Hasan
Md Khaled Hasan
Md. Shamim AhsanMd. Shamim Ahsan
Md. Shamim Ahsan
AMAbdullah- Al- Mamun
Abdullah- Al- Mamun
S. H. Shah NewazS. H. Shah Newaz
S. H. Shah Newaz
Gyu Myoung LeeGyu Myoung Lee
Gyu Myoung Lee
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.

1 January 2013 in Applied Surface Science
Verified
Journal Article
Closed access
Md. Shamim AhsanMd. Shamim Ahsan
Md. Shamim Ahsan
FDFadia Dewanda
Fadia Dewanda
MLMan Seop Lee
Man Seop Lee
HSHitoshi Sekita
Hitoshi Sekita
TSTetsumi Sumiyoshi
Tetsumi Sumiyoshi

1 December 2015 in Optics & Laser Technology
Verified
Journal Article
Closed access
HCHun-Kook Choi
Hun-Kook Choi
Md. Shamim AhsanMd. Shamim Ahsan
Md. Shamim Ahsan
DYDongyoon Yoo
Dongyoon Yoo
ISIk-Bu Sohn
Ik-Bu Sohn
YNYoung-Chul Noh
Young-Chul Noh
HKHo-Min Kang
Ho-Min Kang

10 July 2021 in Plasmonics
Verified
Journal Article
Closed access
PDF file
MRMd. Ekhlasur Rahaman
Md. Ekhlasur Rahaman
RJRayhan Habib Jibon
Rayhan Habib Jibon
Md. Shamim AhsanMd. Shamim Ahsan
Md. Shamim Ahsan
FAFarid Ahmed
Farid Ahmed
ISIk-Bu Sohn
Ik-Bu Sohn