Computer Vision and Deep Learning enthusiast.
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Spam-Classification-using-Streaming-PySpark
November 3, 2021 – December 13, 2021
Team: BD_123_272_313_393
View ProjectAutopilot-on-Airsim
August 22, 2021 – July 28, 2022
Autopilot-on-Airsim — GitHub repository
View ProjectYouTube-Playlist-Length
June 3, 2021 – June 18, 2021
The YouTube Playlist Length web app lets you find out the exact time required to watch a YouTube playlist at various playback speeds.
View ProjectCNNs-from-scratch
April 2, 2021 – April 11, 2021
This is an implementation of a CNN from scratch using numpy
View Project16-bit-Shift-adder-Serial-adder
November 14, 2020 – January 8, 2021
This is a 16 bit shift serial adder written in verilog
View ProjectLow-Cost-Hardware-Accelerated-Vision-Based-Depth-Perception-for-Real-Time-Applications
November 2, 2020 – September 10, 2023
CVMI 2022: A library to simplify disparity calculation and 3D depth map generation from a stereo pair
View ProjectvisionX
March 24, 2020 – March 25, 2020
Objective : To create an automated parking lot management system. Implementation : We would like to use computer vision to tackle the hassles of maintaining a large chain of multi-storeyed parking lots. For this, we would like to use popular python libraries like OpenCV-python, numpy, pandas, etc. Let us consider a large parking lot chain with services that one could subscribe to. Upon request of a subscriber, we could direct him to the nearest parking lot that has room for his/her vehicle. Upon entry to the parking lot (after security screening) a camera would scan the vehicle for the subscriber's details. Parallelly, the parking lot management system would scan the entire lot (using a few ceiling-mounted cameras) for empty spots and directs the verified user to the nearest empty parking spot. Upon exit from the lot, the vehicle is scanned again and the user is charged according to the time of stay. This entire operation will be completed without any human dependency and is completely
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and academic, showcasing a strong interest in diverse technical areas like computer vision, data analytics, and hardware design. However, without information on team-based projects, open-source contributions, or community involvement, it is difficult to fully assess cultural fit for a collaborative software engineering environment. The projects are varied but lack clear alignment with a typical senior software engineer role focused on scalable systems or enterprise applications.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions indicate an ability to work on diverse technical challenges, but there is no information on collaboration, communication, or problem-solving approaches in a team setting.