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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | BLOOD CANCER DETECTION USING DEEP LEARNING MODELS |
| Authors Name: | VITHYA R , Kumaran E , Mathivanan T , Santha Kumar K , Siva P |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_195192
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| Published Paper Id: | IJNRD2305402 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | Leukemia is a fatal order of cancer- related complaint that affects individualities of all periods, including children and grown-ups, and is a significant cause of death worldwide. Particularly, it's associated with White Blood Cells( WBC). thus, a rapid-fire and dependable cancer opinion is a critical demand for successful remedy to raise survival rates. presently, a homemade analysis of blood samples attained through bitsy images is done to diagnose this complaint, which is frequently veritably slow, time- consuming, and less accurate. To address this issues, Convolutional neural network( CNN) with deep infrastructures is being applied as it performs automatic point birth and learns complex high- position features in image bracket operations. This work proposed a different deep literacy models similar as Alexnet, Google Net and VGG- 16 models to classify white blood cell leukemia on intimately available dataset. The results demonstrated that the proposed CNN models are effective in leukemia cells bracket. |
| Keywords: | CNN( complication Neural Network), ANN( Artificial Neural Networks), WBC( White Blood Cells), UML( Unified Modeling Language), VGG( Visual figure Group), ACC( Accurate). |
| Cite Article: | "BLOOD CANCER DETECTION USING DEEP LEARNING MODELS", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.e4-e15, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305402.pdf |
| Downloads: | 000118747 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2305402 Registration ID: 195192 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): Page No: e4-e15 Country: KANCHIPURAM, TAMILNADU, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2305402 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2305402 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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