Dr Mohammed Shafeeq Ahmed

@gug.ac.in

Lecturer, Department of Computer Science
Gulbarga University, Gulbarga



              

https://researchid.co/mdshafeeqahmed

EDUCATION

I received the B.Sc. Computer Science in 2006, from Gulbarga University, Gulbarga, M.C.A. in 2009, from Gulbarga University, Gulbarga, and has awarded Ph.D. in 2022, from Bharathiar University, Coimbatore, India.

RESEARCH INTERESTS

Image Processing, Computer Network, Cyber Security, Software Engineering, Big Data, Data Mining & AI.

4

Scopus Publications

25

Scholar Citations

3

Scholar h-index

Scopus Publications

  • Integration of Artificial Intelligence for a low-cost diagnosis of Diabetic Retinopathy
    Mohammed Shafeeq Ahmed, Tiruvedula Mithun, Regonda Nagaraju, Y Sowmya Reddy, Walunj Madhukar Baban, and Sushma Jaiswal
    IEEE
    Patients with Diabetic Retinopathy (DR) who do not receive appropriate diagnosis and treatment may go blind as the disease affects the retina's blood vessels. Diabetic retinopathy disease must be detected and diagnosed early if the patient's vision is to be preserved. Specifically, this research focuses on digital image analysis, which has huge benefits in terms of both time and money savings, as well as giving more objective measurements than current observer-driven systems and decreasing the workload required from manually taught graders.

  • Detection and classification of exudates by extracting the area from RGB fundus images



  • Detection of exudates from RGB fundus images using 3σ control method
    Mohammed Shafeeq Ahmed and Baddam Indira
    IEEE
    Diabetic Retinopathy (DR) is characterized by color based pathologies. The fundus camera generates fundus image in RGB color and ophthalmologist analyze that image and mark the pathologies to diagnose level of DR. Early detection of exudates from retinal images can potentially reduces the risk of blindness of people suffering from DR. The aim of the work presented in this paper is to detect the exudates (yellowish fat deposit on the retinal surface) from fundus images in RGB color space, thereby facilitate a realistic diagnosis close to the method adopted by ophthalmologist. A Statistical measure-three sigma is used to compute the color intensity range of exudates pixels. The retinal images are preprocessed to enhance the color intensity and optic disk (OD) is eliminated because, it shares similar features with exudates. The aim and objective of this paper is to detect the exudates from RGB fundus images, the pre-processed images are then classified based on the information extracted from three-sigma control method. The results so obtained are promising and also facilitates the ophthalmologist in diagnosing the disease.

RECENT SCHOLAR PUBLICATIONS

  • Integration of Artificial Intelligence for a low-cost diagnosis of Diabetic Retinopathy
    MS Ahmed, T Mithun, R Nagaraju, YS Reddy, WM Baban, S Jaiswal
    2021 5th International Conference on Electronics, Communication and 2021

  • Detection and Classification of Exudates by Extracting the Area from RGB Fundus Images
    MS Ahmed, B Indira
    International Journal of Recent Technology and Engineering (IJRTE) 8 (1 2019

  • Comparative Study on Localization of Optic disc from RGB Fundus Images
    DBI Mohammed Shafeeq Ahmed
    International Journal of Emerging Trends and Technology in Computer Science 2017

  • Detection and Classification of Non-Proliferative Diabetic Retinopathy Stages Using Morphological Operations and SVM Classifier
    DBI Mohammed Shafeeq Ahmed
    2nd International Conference for Convergence in Technology 2017

  • Morphological technique for detection of microaneurysms from RGB fundus images
    MS Ahmed, B Indira
    2017 International Conference on Wireless Communications, Signal Processing 2017

  • Detection of exudates from RGB fundus images using 3σ control method
    MS Ahmed, B Indira
    2017 International Conference on Wireless Communications, Signal Processing 2017

  • A Study on Automatic Segmentation of Optic Disc in Retinal Fundus Images
    MS Ahmed, B Indira
    International Journal of Computer Trends and Technology (IJCTT) 40 (1), 10-16 2016

  • A SURVEY ON AUTOMATIC DETECTION OF DIABETIC RETINOPATHY
    DBI Mohammed Shafeeq Ahmed
    International Journal of Computer Engineering & Technology (IJCET) 6 (Issue 2015

  • A Study on IEEE 802.16 (WiMAX) And Its Security Issues
    MS Ahmed
    International Journal of Advanced Technology & Engineering Research (IJATER 2014

  • PERFORMANCE AND EVALUATION OF FREQUENT ITEMSETS USING FP-GROWTH AND HUI TECHNIQUE IN DATA MINING
    MS Ahmed
    International Journal of Functional Management 6 (2), 206-209 2013

  • DATA WAREHOUSING APPLICATIONS: AN ANALYTICAL TOOL FOR DECISION SUPPORT SYSTEM
    MS AHMED
    International Journal of Computer Science and Informatics 3 (1), 11-16 2013

  • PERFORMANCE EVALUATION AND ENHANCEMENT OF THE INITIAL RANGING MECHANISM IN MAC 802.16 FOR WIMAX NETWORKS USING NS-2
    MS AHMED
    INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATION & MANAGEMENT 2 (7 2012

  • Network Security Using Cryptographic Mechanism
    MS Ahmed
    Opportunities & Challenges for Future Managers 2011

  • Medical Image Edge Detection on Object Recognition of Human Organs Based on Mathematical Morphology Theory
    MS Ahmed
    Recent Trends in Computer Technology 2, 167-170 2011

  • Database Security in Network Based Environment
    MS Ahmed
    BIZTECH, 29-35 2011

  • A survey on dynamic clustering based colour image segmentation using genetic algorithm
    MS Ahmed
    World Journal of Science and Technology 1 (12), 35-41 2011

MOST CITED SCHOLAR PUBLICATIONS

  • A SURVEY ON AUTOMATIC DETECTION OF DIABETIC RETINOPATHY
    DBI Mohammed Shafeeq Ahmed
    International Journal of Computer Engineering & Technology (IJCET) 6 (Issue 2015
    Citations: 8

  • Morphological technique for detection of microaneurysms from RGB fundus images
    MS Ahmed, B Indira
    2017 International Conference on Wireless Communications, Signal Processing 2017
    Citations: 6

  • Detection of exudates from RGB fundus images using 3σ control method
    MS Ahmed, B Indira
    2017 International Conference on Wireless Communications, Signal Processing 2017
    Citations: 6

  • A survey on dynamic clustering based colour image segmentation using genetic algorithm
    MS Ahmed
    World Journal of Science and Technology 1 (12), 35-41 2011
    Citations: 3

  • Integration of Artificial Intelligence for a low-cost diagnosis of Diabetic Retinopathy
    MS Ahmed, T Mithun, R Nagaraju, YS Reddy, WM Baban, S Jaiswal
    2021 5th International Conference on Electronics, Communication and 2021
    Citations: 2

Publications

1. Detection and Classification of Diabetic Retinopathy from Fundus Images using Optimized 3 Sigma and NN. (Application No. 202241000469, Journal No. 05/2022, pp. no 6187, dated 04/02/2022).
2. Auto Encoder Deep Convolutional Neural Network and Machine Learning Approaches for Image Retrieval System. (Application No. 202111055040, Journal No. 49/2021, pp. no 57834, dated 03/12/2021).
3. Reliability Control using Loss Recovery Techniques in Wireless Sensor Network. (Application No. 202121052948, Journal No. 48/2021, pp. no 56292, dated 26/11/2021).