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Dr. Saqib Qamar

Qualification : Ph.D.

Details of Educational Qualification:

Course Specialization Group College Name/University Year of Passing
Ph.D. Computer Science Computer Science Huazhong University of Science and Technology (HUST), China 2019
M.C.A. Computer Applications Computer Applications Aligarh Muslim University, Aligarh, India 2013
B.Sc. Statistics (Hons.) B.Sc. Aligarh Muslim University, Aligarh, India 2010

Note : Students are advised to meet me in Room No : WB - 214 at any time other than my class hours mentioned in the below timetable for any discussions related to the subjects & research.

My Schedule for 2020-21

                                     

My Publications

S.No Title of the Paper Full Details of Journal Name / Conference Name, Volume number, page number, Date
1 “Multi stream 3D hyper-densely connected network for multi modality isointense infant brain MRI segmentation", Multimedia Tools and Applications(MTA),2019, 78(18):25807-25828 (SCI )Saqib Qamar, Hai Jin, Parvez Ahmad “A Variant Form of 3D-UNet for Infant Brain Segmentation", Future Generation Computer Systems (FGCS), https://doi.org/10.1016/j.future.2019.11.021
2 “Dense Encoder-Decoder based architecture for skin lesion segmentation", Cognitive Computation (Accepted)(SCI)
3 “Single binding of data and model parallelisms to parallelize convolutional neural networks through multiple machines”. Journal of Intelligent and Fuzzy Systems (JIFS), 2018,35(5):5449-5466.(SCI)
4 ” Techniques of Data Mining In Health care: A Review”, International Journal of Computer Applications 120(15):38-50, June 2015.
5 ” Emotion detection from Text Using Fuzzy logic”, International Journal of Computer Applications 121(3):29-33, July 2015
6 "Hybrid Labels for Brain Tumor Segmentation" In: Crimi A., Bakas S. (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2019. Lecture Notes in Computer Science, vol 11993. Springer, Cham,( MICCAI 2019)
7 “3D Hyper-dense Connected Convolutional Neural Network for Brain Tumor Segmentation”. In: Proceeding of 14th International Conference on Semantics, Knowledge and Grids (SKG), Guangzhou, China,IEEE,2018. (IEEE Xplore, Ei,Scopus)
8 “Hybrid loss guided densely connected convolutional neural network for Ischemic Stroke Lesion segmentation”. IEEE, International Conference for Convergence on Technology (I2CT),2019.(IEEE Xplore, Ei, Scopus)
9 “Dense dialated Hierarchical Architecture for Brain Tumor Segmentation” ICBDC 2019, Guangzhou, China. (ACM Archive, Ei,Scopus)
10 “Combined 3D CNN for Brain Tumor Segmentation ”MIPR2020, Shenzhen, China.(CCF)(IEEE Xplore, Ei, Scopus)