Shrijeet Bharatbhushan Pagrut

@ssgmce.ac.in

Assistant Professor, CSE
Shri Sant Gajanan Maharaj College od Engineering, Shegaon

Shrijeet Bharatbhushan Pagrut


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https://researchid.co/shreepagrut

RESEARCH, TEACHING, or OTHER INTERESTS

Multidisciplinary, Computer Engineering, Education, Multidisciplinary
2

Scopus Publications

1

Scholar Citations

1

Scholar h-index

Scopus Publications

  • SyVCO-RSYv5: Rolling Shutter Based Deep Learning Model for Obstacle Detection and Distance Measurement for Low-Flying Drones
    Shrijeet Pagrut, Pradip Jawandhiya
    International Journal of Image and Graphics, 2025
    Vision-based detection technologies have been raised as a useful technology for analyzing the surroundings to ensure overall safety. The obstacle detection enhances the precision of navigation and reduces collisions in low-flying drones. Conventional autonomous detection models are susceptible to various challenges, including complexities, parameter extraction, and lighting conditions. Therefore, in this research, the Synergic and Vigilance Cuculidae Optimized–Rolling Shutter based You Only Look Once-V5 (SyVCO-RSYv5) model is developed, which overcomes the real-time complexities and amplifies the detection outcome. Specifically, the optimal selection of model parameters using the SyVCO algorithm significantly enhances the performance and stability of the system, thus better adapting the proposed model to complex scenarios. Further, the incorporation of rolling shutter-based distance measurement accurately computes the distance of the detected object. Besides, the denoising performance is enhanced with the optimized vision transformer, which improves the detection performance. Further, the Multimodal Residual Invariant Feature Mapping (MRIM) method provides a robust representation of images for analyzing the obstacles in complex scenarios. When compared with other methods, the results show the enhanced efficacy of the system with an accuracy of 96.61%, specificity of 97.40%, and sensitivity of 94.80% with 80% training.
  • Unmanned Aerial Vehicles and Low-Flying Drones: A Review of Classification
    Shrijeet Pagrut, Pradip Jawandhiya
    2024 2nd Dmiher International Conference on Artificial Intelligence in Healthcare Education and Industry Idicaiei 2024, 2024
    Nowadays Research and Development of Novel and Efficient drones becomes the core part of strategic practices of every nation. There is a growing need of using a variety of Unmanned Aerial Vehicles with significant capabilities in Civilian, Military and Commercial Applications. UAVs flight patterns such as Vertical Takeoff Landing and Horizontal Takeoff Landing, its maximum altitude capacity, range are discussed. Designing of Low Flying drones are classified into Small, Micro and Nano-Pico-SmartDust(NPSD) categories. Use and Impact of different materials like Titanium alloy in design is provided. Additionally, current activities in the market related to small drones and future research direction in the field of utility and applications drones are discussed.

RECENT SCHOLAR PUBLICATIONS

  • SyVCO-RSYv5: Rolling Shutter Based Deep Learning Model for Obstacle Detection and Distance Measurement for Low-Flying Drones
    S Pagrut, P Jawandhiya
    International Journal of Image and Graphics, 2750085 , 2025
    2025
  • Unmanned Aerial Vehicles and Low-Flying Drones: A Review of Classification
    S Pagrut, P Jawandhiya
    2024 2nd DMIHER International Conference on Artificial Intelligence in … , 2024
    2024
  • Plant disease detection using mask RCNN
    CB Junare, VS Ghanokar, RM Khandare, SP Koche, SB Pagrut
    SSGM Journal of Science and Engineering 2 (1), 21-26 , 2024
    2024
    Citations: 1
  • Forensic Analysis for Effective Combine Attack Management System Based on Cloud Computing
    SB Pagrut, CJ Shelke
    computing 3 (2) , 2014
    2014

MOST CITED SCHOLAR PUBLICATIONS

  • Plant disease detection using mask RCNN
    CB Junare, VS Ghanokar, RM Khandare, SP Koche, SB Pagrut
    SSGM Journal of Science and Engineering 2 (1), 21-26 , 2024
    2024
    Citations: 1
  • SyVCO-RSYv5: Rolling Shutter Based Deep Learning Model for Obstacle Detection and Distance Measurement for Low-Flying Drones
    S Pagrut, P Jawandhiya
    International Journal of Image and Graphics, 2750085 , 2025
    2025
  • Unmanned Aerial Vehicles and Low-Flying Drones: A Review of Classification
    S Pagrut, P Jawandhiya
    2024 2nd DMIHER International Conference on Artificial Intelligence in … , 2024
    2024
  • Forensic Analysis for Effective Combine Attack Management System Based on Cloud Computing
    SB Pagrut, CJ Shelke
    computing 3 (2) , 2014
    2014