02 SKILLS
MY KNOWLEDGE LEVEL IN SOFTWARE
01 Education
THIRD YEAR UNDERGRADUATE
Bachelor of Technology, Computer Science and Engineering
Visvesvaraya National Institute of Technology Nagpur, India
LANGUAGES : C, C++, Java, Python
WEB DEVELOPMENT : HTML, CSS, JSP, MySQL
RESEARCH TOOLS & LIBRARIES : OpenCV, Tensorflow, ROS, Matlab, Android, Netlogo
MISC TOOLS : Photoshop, Latex
I'M
Kartik
Paigwar.
Amateur Programmer by day.
Roboticist by night.
An amateur programmer, roboticist garnished with a pinch of creativity.
I like to relate with the things i learnt and simplify the problems that’s what defines me, so what i believe is our hard work isn’t deterministic,it may not always be rewarding though it always adds up to our experience history and we can always scroll up in past and restore back that experience whenever right opportunities hit us.
I enjoy the simple things in life. Being happy is a state of mind, and I don't think people should settle for less than they deserve. I always look toward the next best thing.
Your real strength comes from being the best you YOU can be.
03 PORTFOLIO
04 EXPERIENCE
MY LATEST WORK. SEE MORE >
Network Design Lead
To obtain an all-in-focus image by fusing multiple images of the same scene taken with different focal settings using Deep CNN.
Multi-Focus Image Fusion with a Deep Convolutional Neural Network
Sept' 17 - Present
Vision System Lead
Implemented Navigation stack, a method to make
autonomous robot navigation.Developed vision system 1) For mobile robot to follow the lane with sharp turns.
2)For autonomous navigation to natural landmarks in outdoor situation with the use of a single camera and parabolic mirror to get the 360 field of view.
Turtlebot 2
May'17 - Aug ’17
Team lead
Navigated mobile robot from source to destination by avoiding obstacles using A-star search algorithm for path planning. Localized robot using AprilTag.
AprilTag based localization & autonomous robot navigation using single overhead camera
Jan’17- Mar’17
To prepare the algorithm of the expert system, which
will perform the presumptive diagnosis of two diseases of urinary system.Feed forward neural network was trained and tested using UCL Acute Inflammations Data Set with an accuracy of 94%. Further converted this data set into unsupervised.Then Kohonen Self Organising Maps were used for classification with an accuracy of 84%.
Presumptive diagnosis of acute inflammations of urinary bladder and acute nephritises using Neural Network techniques
Nov’16 -Dec’16
Provided Real time In Air Freehand Drawing experience.
Added utility track-bar to change color, size
and a tool to erase.
Virtual Freehand Drawing Pad
Sept’16 -Oct’16
Small color cubes are detected and their positions are identified with respect to faces of the Rubik's cube.
Used kociemba algorithm for finding the most optimum moves to solve the scrambled cube.
Animated moves with the help of 3D GUI created using OpenGl libraries.
Rubik’s Cube Solver Program
Oct’16 - Nov’16