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          <dc:title>&lt;b&gt;Multi-Class Cervical Cell Analysis in Pap Smear Images&lt;/b&gt;</dc:title>
          <dc:creator>Polisetty Sujatha (25113918)</dc:creator>
          <dc:subject>Cancer diagnosis</dc:subject>
          <dc:subject>cervical cancer continues</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;Multi-class classification and cervical cell segmentation are crucial elements of computer-aided Pap smear image analysis. To handle these tasks, an improved multi-stage deep learning system was created in this research. The proposed approach makes use of Enhanced ResNet-101 for multi-class cervical cell classification, Enhanced UNet for nucleus and cytoplasm segmentation, and AlexNet for deep feature extraction.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-26T08:28:46Z</dc:date>
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