photo
Mr. Mohammad Naved Qureshi
  • DEPARTMENT_STAFF.QUALIFICATION

    M.Tech(Software Engineering)

  • DEPARTMENT_STAFF.DESIGNATION

    Assistant Professor

  • DEPARTMENT_STAFF.THRUST_AREA

    Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Data Analysis

  • DEPARTMENT_STAFF.ADDRESS

  • DEPARTMENT_STAFF.MOBILE

    9411854211

  • DEPARTMENT_STAFF.EMAIL

    naved.ubp@amu.ac.in

  • DEPARTMENT_STAFF.TIME_TABLE

    First & Third SemesterFifth Semester

DEPARTMENT_STAFF.COMPLETE_CV
DEPARTMENT_STAFF.PROFILE

Mr. M. Naved Qureshi is working as an Assistant Professor in the University Polytechnic (Boys), Electrical Engineering Section for teaching Diploma in Computer Engineering courses since Jan 2015. Prior to that, he has worked as Guest faculty in the Department of Computer Engineering, AMU. He is Pursuing a Ph.D. as a teaching Candidate from the Department of Computer Engineering and has done his M.Tech (Software Engineering) from the same department. Mr. Naved has qualified GATE as well as UGC-NET Examination.

  1. Publication

    Book Chapters

    1. Nadeem Akhtar, M.N Qureshi, Mohd Vasim Ahamad, " An Improved Clustering Method for Text Documents Using Neutrosophic Logic”, Springer Nature Singapore Pte Ltd. 2017 R. Ali and M. M. S. Beg (eds.), Applications of Soft Computing for the Web, https://doi.org/10.1007/978-981-10-7098-3_10


    Conference Papers

      1. A. U. S. Khan, M. N. Qureshi and M. A. Qadeer, "Anti-theft application for android based devices," 2014 IEEE International Advance Computing Conference (IACC), 2014, pp. 365-369, DOI: 10.1109/IAdCC.2014.6779350.

      2. Azeem Ush Shan Khan, Nadeem Akhtar, and Qureshi, Mohammad Naved. "Real-Time Credit-Card Fraud Detection using Artificial Neural Network Tuned by Simulated Annealing Algorithm." Paper presented at the meeting of the, 2014.

      3. M. N. Qureshi, H. F. H. Aldheleai and Y. K. Tamandani, "An improved documents classification technique using association rules mining," 2015 IEEE International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), 2015, pp. 460-465, DOI: 10.1109/ICRCICN.2015.7434283.

      4. Qureshi, Mohammad Naved, and Mohd Vasim Ahamad. “An Improved Method for Image Segmentation Using K-Means Clustering with Neutrosophic Logic.” Procedia Computer Science 132 (2018): 534-540.

      5. M. N. Qureshi and M. S. Umar, "Analysis of Different Deep Learning Techniques for The Development of An Efficient CNN Model for Melanoma Skin Cancer Diagnosis," 2022 International Conference for Advancement in Technology (ICONAT), 2022, pp. 1-6, DOI: 10.1109/ICONAT53423.2022.9726072.


    Journals

    1. MN Qureshi, MS Umar, “Performance Evaluation of Novel Convolution Neural Network Architecture for Melanoma Skin Cancer Diagnosis on Different Hardware Processing Units” Journal of Physics: Conference Series, Volume 1950, International Conference on Mechatronics and Artificial Intelligence (ICMAI) 2021 27 February 2021, Gurgaon, India
    2. Qureshi, M.N.; Umar, M.S.; Shahab, S. A Transfer-Learning-Based Novel Convolution Neural Network for Melanoma Classification. Computers 2022, 11, 64. https://doi.org/10.3390/computers11050064



LISTDownloadUPLOADED DATE
BLC 503 Unit 2
10/10/2021
BLC 503 Unit 1_3
10/10/2021
BLC 503 Unit 1_2
10/10/2021
BLC 503 Unit 1_1
10/10/2021
BLC 503 Unit 3
21/10/2021
PEE291C_IT_Lab_Syllabi
21/10/2021
PEE291C_Module1.1
21/10/2021
PEE291C_Module1.2
21/10/2021
PEE291C_Module2.1
21/10/2021
BLC503 Google Drive Link For Attendance and Video Lectures
24/10/2021