{"id":226,"date":"2024-08-26T18:00:00","date_gmt":"2024-08-26T22:00:00","guid":{"rendered":"https:\/\/carleton.ca\/richarddansereau\/?p=226"},"modified":"2025-12-08T12:30:41","modified_gmt":"2025-12-08T17:30:41","slug":"shaad-fazal-defends-his-masc-thesis","status":"publish","type":"post","link":"https:\/\/carleton.ca\/richarddansereau\/2024\/shaad-fazal-defends-his-masc-thesis\/","title":{"rendered":"Shaad Fazal defends his MASc thesis"},"content":{"rendered":"<table style=\"border-collapse: collapse; width: 100%;\">\n<tbody>\n<tr>\n<td style=\"width: 30%;\">\n<h3><img decoding=\"async\" loading=\"lazy\" class=\"alignnone size-medium wp-image-236\" src=\"https:\/\/carleton.ca\/richarddansereau\/wp-content\/uploads\/Shaad-Figure-1-240x406.png\" alt=\"Figure showing example separation of overlapping cells.\" width=\"240\" height=\"406\" srcset=\"https:\/\/carleton.ca\/richarddansereau\/wp-content\/uploads\/Shaad-Figure-1-240x406.png 240w, https:\/\/carleton.ca\/richarddansereau\/wp-content\/uploads\/Shaad-Figure-1-160x270.png 160w, https:\/\/carleton.ca\/richarddansereau\/wp-content\/uploads\/Shaad-Figure-1.png 300w\" sizes=\"(max-width: 240px) 100vw, 240px\" \/><\/h3>\n<\/td>\n<td style=\"width: 70%;\">\n<h3>Shaad successfully defended his MASc thesis:<\/h3>\n<blockquote>\n<h4><b>Cervical Cell Separation using Deep Learning Techniques.<\/b><\/h4>\n<\/blockquote>\n<p>This research introduced a deep learning-based pipeline for separating overlapping cervical cells in cytology images, leveraging advanced segmentation and generative models to produce clear, individual cell images. This approach significantly improves diagnostic accuracy and outperforms existing techniques.<\/p>\n<p>Congratulations Shaad Fazal!<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Shaad successfully defended his MASc thesis: Cervical Cell Separation using Deep Learning Techniques. This research introduced a deep learning-based pipeline for separating overlapping cervical cells in cytology images, leveraging advanced segmentation and generative models to produce clear, individual cell images. This approach significantly improves diagnostic accuracy and outperforms existing techniques. Congratulations Shaad Fazal!<\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","_mi_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[22,1],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Shaad Fazal defends his MASc thesis - Prof. Richard M. 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