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                <text>Book Chapter</text>
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              <text>Removal of Occlusion in Face Images Using PIX2PIX Technique for Face Recognition</text>
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              <text>Face recognition system; Occlusion; Pix2pix</text>
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              <text>Occlusion of face images is a serious problem encountered by the researchers working in different areas. Occluded face creates a hindrance in extracting the features thereby exploits the face recognition systems. Level of complexity increases with changing gestures, different poses, and expression. Occlusion of the face is one of the seldom touched areas. In this paper, an attempt is made to recover face images from occlusion using deep learning techniques. Pix2pix a condition generative adversarial network is used for image recovery. This method is used for the translation of one image to another by converting an occluded image to a non-occluded image. Webface-OCC dataset is used for experimentation, and the efficacy of the proposed method is demonstrated.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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              <text>John S.; Danti A.</text>
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              <text>Lecture Notes on Data Engineering and Communications Technologies, Vol-111, pp. 47-57.</text>
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              <text>Springer Science and Business Media Deutschland GmbH</text>
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              <text>2022-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-16-9113-3_5" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-16-9113-3_5&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133519159&amp;amp;doi=10.1007%2F978-981-16-9113-3_5&amp;amp;partnerID=40&amp;amp;md5=364f317fec08eec196596e6eb9db8444" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133519159&amp;amp;doi=10.1007%2f978-981-16-9113-3_5&amp;amp;partnerID=40&amp;amp;md5=364f317fec08eec196596e6eb9db8444&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISSN: 23674512</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>John S., Department of Computer Science and Engineering, Christ (Deemed To Be) University, Bangalore, India; Danti A., Department of Computer Science and Engineering, Christ (Deemed To Be) University, Bangalore, India</text>
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