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Facial Analysis Using Deep Learning

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Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 33))

Abstract

A face search system which merges a live search strategy along with a state-of-the-art commercial-off the shelf (COTS) matcher, one cascaded framework. In this first sort massive album of photos, to figure out the top-k most alike faces. The k retrieved prospect is re-ranked by emerging equalities depending on deep features and those results by the COTS matcher. The software based technique is complex and large. It analysis unique shape, pattern and positioning to the respective facial features. It estimates with the records consists of images present in central or local database, the deep network representation combines with a state-of-the-art as well as COTS face matcher in large-scale face search system. According to study on the face datasets leads to complexity: LFW dataset (consist of face detectable). In this project Viola-Jones face detector algorithm is used. The Viola-Jones Technique use to perform feature extraction and evaluation the Rectangular features measures with a new image representation their calculation is very fast.

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References

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Correspondence to Priyanka More , Poonam Desale , Mayuri S. Gothwal , Pradnya S. Sahajrao or Aarzoo A. Shaikh .

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More, P., Desale, P., Gothwal, M.S., Sahajrao, P.S., Shaikh, A.A. (2020). Facial Analysis Using Deep Learning. In: Balaji, S., Rocha, Á., Chung, YN. (eds) Intelligent Communication Technologies and Virtual Mobile Networks. ICICV 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 33. Springer, Cham. https://doi.org/10.1007/978-3-030-28364-3_4

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  • DOI: https://doi.org/10.1007/978-3-030-28364-3_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-28363-6

  • Online ISBN: 978-3-030-28364-3

  • eBook Packages: EngineeringEngineering (R0)

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