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In preprocessing, synthetic images are generated using a generative adversarial network (GAN) and normalized by color transformation. The optimal deep features are extracted from each blood smear image using pretrained deep models i.e., DarkNet-53 and ShuffleNet. More informative features are selected by principal component analysis (PCA) and fused serially for classification. The morphological operations based on color thresholding with the deep semantic method are utilized for leukemia segmentation of classified cells. The classification accuracy achieved with ALL-IDB and LISC dataset is 100% and 99.70% for the classification of leukocytes i.e., blast, no blast, basophils, neutrophils, eosinophils, lymphocytes, and monocytes, respectively. Whereas semantic segmentation achieved 99.10% and 98.60% for average and global accuracy, respectively. The proposed method achieved outstanding outcomes as compared to the latest existing research works.<\/jats:p>","DOI":"10.1007\/s40747-021-00473-z","type":"journal-article","created":{"date-parts":[[2021,7,28]],"date-time":"2021-07-28T09:03:14Z","timestamp":1627462994000},"page":"3105-3120","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":73,"title":["A deep network designed for segmentation and classification of leukemia using fusion of the transfer learning models"],"prefix":"10.1007","volume":"8","author":[{"given":"Saba","family":"Saleem","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1080-5446","authenticated-orcid":false,"given":"Javeria","family":"Amin","sequence":"additional","affiliation":[]},{"given":"Muhammad","family":"Sharif","sequence":"additional","affiliation":[]},{"given":"Muhammad Almas","family":"Anjum","sequence":"additional","affiliation":[]},{"given":"Muhammad","family":"Iqbal","sequence":"additional","affiliation":[]},{"given":"Shui-Hua","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,7,28]]},"reference":[{"key":"473_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-018-33738-8","volume":"8","author":"D-H Kuan","year":"2018","unstructured":"Kuan D-H, Wu C-C, Su W-Y, Huang N-T (2018) A microfluidic device for simultaneous extraction of plasma, red blood cells, and on-chip white blood cell trapping. 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