MUKESH Sadhasivam

- Yolov3 Object detection- Spearheaded the development of a vehicle detection and tracking system using YOLOv3 and OpenCV, achieving high accuracy in vehicle identification and counting from video footage.

-Advanced Video analysis - Implemented frame-by-frame vehicle tracking in pre-recorded video, utilizing bounding box and confidence thresholding techniques for precise detection and real-time vehicle count display

-Optimization and Collaboration - Optimized YOLOv3-based object detection models for Raspberry Pi 4, collaborating with industry experts for enhanced performance in aerial surveillance applications.

-Deep Learning Framework Proficiency-Excelled in distinguishing and optimizing various deep learning frameworks, focusing on efficient model selection and performance enhancement for specific hardware constraints.

-Model Handling And Edge Computing - Gained significant experience in model handling and optimization using Intel's OpenVINO toolkit, contributing to advancements in edge computing.

-Project Demonstration - View my project on Face Detection and Tracking, implemented in Raspberry Pi 4 using the OpenVINO toolkit. This video showcases the prototype model and live detection capabilities tested on the Raspberry Pi 4 as a preliminary stage before its integration into the live drone application. https://www.youtube.com/watch?v=_kIqQmBJfj0

-Piezoresistive sensor development -Contributed to the design of piezoresistive sensors for aerospace, emphasizing problem-solving in sensor performance optimization.

-Stimulation and Analysis - Excelled in utilizing COMSOL and MATLAB for in-depth sensor analysis, focusing on critical aspects of electrical potential, deflection, and noise factor evaluation.

-Research Methodology Proficiency- Demonstrated expertise in systematic research approaches, conducting comprehensive studies and simulations to enhance technological applications in aerospace and robotics.

-International Team Collaboration - Demonstrated effective teamwork in a multicultural research environment, enhancing project outcomes through diverse perspectives.

-Real-world testing Skills - Skillfully translated theoretical concepts into real-world testing and analysis, including wind tunnel experiments and sensory data evaluation for aerospace application