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Miss. Yusra Meraj
  • DEPARTMENT_STAFF.QUALIFICATION

    B.Tech(Electronics and Communication Engineering), MTech (Communication and Information Systems)

  • DEPARTMENT_STAFF.DESIGNATION

    Guest Faculty

  • DEPARTMENT_STAFF.THRUST_AREA

    Low memory image coders for IoT/visual sensor nodes, Image quality assessment

  • DEPARTMENT_STAFF.ADDRESS

    4/1175J, New Sir Syed Nagar, Aligarh

  • DEPARTMENT_STAFF.MOBILE

    8267008469 ,

  • DEPARTMENT_STAFF.EMAIL

    gf1823@myamu.ac.in ,

  • DEPARTMENT_STAFF.TIME_TABLE

    Time table

DEPARTMENT_STAFF.COMPLETE_CV
Ms. Yusra Meraj received M.Tech (Communication and Information Systems) and B.Tech (Electronics and Communication Engineering) degrees in the year 2020 and 2018, respectively 
from the Department of Electronics Engineering, Aligarh Muslim University, Aligarh, India
Presently she is employed as a Guest Faculty in Electronics Engineering Section at University Women's Polytechnic, AMU, Aligarh from April 2021 to date. She is GATE qualified and is a recipient of the prestigious Sir Syed Global Scholarship Award. Her research areas include Image Quality Assessment, Low Memory image Coders for Visual Sensors/IoT nodes. She has received Best Paper Award and Mathworks Best Impact Paper Award for her work.


  1. A block-based parallel ZM-SPECK algorithm

    The Zero Memory Set Partitioned Embedded Block (ZM-SPECK) algorithm is an embedded and memory-efficient image compression algorithm. However, it is computationally complex due to the recursive significance testing of sets and coefficients in each bit plane. To overcome this limitation, it is proposed to parallelize the algorithm over smaller blocks to reduce the overall encoding and decoding times of the ZM-SPECK algorithm. The proposed approach called block-based parallel ZM-SPECK (BPZM-SPECK) decomposes the wavelet transformed image into independent non-overlapping spatial blocks utilizing the unique child-parent relationships in spatial orientation trees (in wavelet domain) and simultaneously encodes all bits in each bit plane of a block. The experimental results show significant improvement in computation time over the existing ZM-SPECK algorithm.


  2. Modified ZM-SPECK: A Low Complexity and Low Memory Wavelet Image Coder for VS/IoT Nodes

    The Zero Memory Set Partitioned Embedded Block (ZM-SPECK) algorithm is a memory-efficient block-based image coder used to encode the wavelet transformed images. It is a listless form of the SPECK algorithm and has no provision for saving the significance information for various coefficients/sets. Since it performs significance testing of sets recursively at each bit-plane, therefore it is computationally complex. Due to this limitation, it is difficult to implement it on low-resource sensor/IoT nodes. In this paper, its low complexity version named Modified Zero Memory Set Partitioned Embedded Block (MZM-SPECK) is proposed which reduces the recursive significance test of sets. The simulation results indicate that the proposed algorithm surpasses other wavelet-based coders with regard to memory and computational complexity while maintaining excellent coding efficiency.


LISTDownloadUPLOADED DATE
Assignment 3 of NSFC
05/04/2022
Assignment 2 of NSFC
21/03/2022
Unit 3 Active Filters
05/04/2022
Unit 3 Transistor Biasing
09/03/2022
Syllabus of Electronic Devices and Circuits-II
02/12/2021
Unit-1 Bipolar Junction Transistor
02/12/2021
Unit- 2 Field Effect Transistor
11/01/2022
Syllabus of Network Synthesis & Filter Circuits
28/01/2022
Unit-1 NETWORK FUNCTIONS AND THEIR REALIZABILITY
28/01/2022
Assignment 1 of NSFC
28/01/2022
Assignment 3 of EDC-II
28/01/2022
Assignment 4 of EDC-II
04/02/2022
Unit-4 OPERATIONAL AMPLIFIER & ITS APPLICATIONS
14/02/2022
Unit 2 PASSIVE NETWORK SYNTHESIS
28/02/2022
Assignment 5 of EDC-II
03/03/2022
Assignment 4 of NSFC
16/04/2022
Unit 4 Basics of Active Filter Synthesis
17/04/2022