Blood Group:
Assistant Professor
Phone: +8801762899397
E-mail: sakifaaktar133089@gmail.com
Address:
Current Research working Topic
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Short Biography
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Current Research
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Research Interests
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Image Processing, Deep Learning, Computer Vision, AI
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B.Sc. (Eng.) from RUET |
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Student Guidance
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Course Taught(Under Gradute, Graduate)
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Course Material
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| Publication Type | Publication Title | Published Year |
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| Journal Articles | Sakifa Aktar; Ashis Talukder; Md. Martuza Ahamad; A. H. M. Kamal; Jahidur Rahman Khan; Md. Protikuzzaman; Nasif Hossain; Salem A. Alyami; AKM Azad; Julian M.W. Quinn; Mathew A. Summers; Teng Liaw; Valsamma Eapen and Mohammad Ali Moni. (2021).Machine Learning Approaches to Identify Patient Comorbidities and Symptoms That Increased Risk of Mortality in COVID-19. Diagnostics, 11, 8:1383. View | 2021 |
| Journal Articles | Sakifa Aktar; Md. Martuza Ahamad; Md. Rashed-Al-Mahfuz; Shahadat Uddin; A H M Kamal; SalemA. Alyami; Ping-I Lin; Sheikh Mohammad Shariful Islam; Julian M.W. Quinn; Valsamma Eapen and Mohammad Ali Moni. (2021). Machine Learning Approach to Predicting COVID-19 Disease Severity Based on Clinical Blood Test Data: Statistical Analysis and Model Development. JMIR Medical Informatics, Publisher: Journal of Medical Internet Research. View | 2021 |
| Conference | Nayeem Hossain; Md. Martuza Ahamad; Sakifa Aktar and Mohammad Ali Moni. (2021). Movie Genre Classification with Deep Neural Network using Poster Images. In International conference on information and communication technology for sustainable development (ICICTSD2020) (pp.195–199). View | 2021 |
| Journal Articles | Md. Martuza Ahamad; Sakifa Aktar; Md. Rashed-Al-Mahfuz; Shahadat Uddin; Pietro Liò; Haoming Xu; Matthew A. Summers; Julian M.W. Quinn and Mohammad Ali Moni. (2020). A machine learning model to identify early stage symptoms of SARS-Cov-2 infected patients. Expert Systems with Applications, Publisher: Elsevier, 160, 113661. View | 2020 |
| Conference | Sakifa Aktar, Mamun, M. A., Multi-View 3D Object Retrieval using Autoencoder & Deep Embedding Network, International Conference on Electrical, Computer and Communication Engineering (ECCE), Chittagong University of Engineering and Technology, Cox’s Bazar, Bangladesh. View | 2019 |
| Conference | Sakifa Aktar, Mamun, M. A., Hossain, M. A Comparative Study of Multi-View 3D Object Retrieval with Autoencoder & Deep Embed-ding Network, 21st International Conference of Computer and Information Technology (ICCIT), United International University, Dhaka, Bangladesh. View | 2018 |
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