Organized and dependable candidate successful at managing multiple priorities with a positive attitude. Willingness to take on added responsibilities to meet team goals.
Organized and dependable candidate successful at managing multiple priorities with a positive attitude. Willingness to take on added responsibilities to meet team goals.
Marks Obtained: 9.5/10 CPI
B.Tech. Final Year Project- Detection of enhancement based tampering in digital images
About the Project: Developed an Image Classifier using MATLAB to Detect enhancement-based Tampering in Digital Images. Proposed Classifier achieved accuracy around 95% with available Data set
B.Tech. Pre-Final Year Report- Advancement in artificial intelligence and its impact
About the Project: Written a Report of impact of artificial intelligence on different Sectors
Marks Obtained: 88.8%
Project Title- Design of variable Gain Instrumentation Amplifier
About the Project: Designed and Implemented precise and accurate variable gain amplifier
Marks Obtained: 80.5%
C/C, Python
Saqib Qamar, Hai Jin, Mohd Faizan “Hybrid loss guided densely connected convolutional neural network for Ischemic Stroke Lesion segmentation”. IEEE, International Conference for Convergence on Technology (I2CT), 2019
Father’s Name: Faiz Mohammad
Permanent Address: Westside, Jalalpur, Ambedkar Nager
D.O.B October 09, 1996
Marital Status: Single
Nationality: Indian
Interest/Hobbies: Cricket, Football, Chess
Completed C++ Nano Degree program from Udacity
Saqib Qamar, Hai Jin, Mohd Faizan “Lighter 3D Encoder-Decoder Architecture for Brain Tumor Segmentation”, IEEE Access
Saqib Qamar, Hai Jin, Mohd Faizan “Hybrid loss guided densely connected convolutional neural network for Ischemic Stroke Lesion segmentation”. IEEE, International Conference for Convergence on Technology (I2CT), 2019
Participated in pre-conference tutorials on “Advances in Wireless technology” from 24-26 November 2017 conducted by Department of Electronics Engineering, Aligarh Muslim University.
ELEC1200.2x: A System View of Communications: From Signals to Packets conducted by Hong Kong University of science and technology on Edx Platform