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Non-photorealistic-Speedlines
January 29, 2018 – January 29, 2018
We present an experimental algorithm to summarize motion of multiple objects in a short video into a single image. This depiction of this motion path is done with the help of speedlines. This reduces the amount of data, as compared to storing an image that conveys the same information as a video.By tracking the edges of the moving objects in the frames,we attempt to draw the motion lines at their rear edges. With the help of some techniques mentioned in existing literature, we detect the rear edges across multiple frames and record their paths. With these coordinates speed-lines are built as a straight-line or curved path. We also look at the applications for such a method and also provide results of our experiments along with some ideas for future applications.
View ProjectMobile-Distributed-File-System-DFS2
November 6, 2017 – November 6, 2017
Mobile-Distributed-File-System-DFS2 — GitHub repository
View ProjectFortify-X10
June 16, 2017 – July 6, 2017
Implementing Parallel Programming Abstraction of Fortress in X10
View ProjectFortify-XTend
May 24, 2017 – June 6, 2017
Implementing parallelism abstractions from Fortress into Xtend
View ProjectInformation-Inference-and-Learning
January 22, 2017 – January 22, 2017
Classroom assignments for Information Theory, Inference and Learning
View ProjectSPONJ
September 3, 2016 – August 2, 2017
Submission Portal and Online Judge is a web application which provides a way of taking Lab/Tutorials assignments. This web application provides Professor, Teaching assistant and Student can login with their predefined permission.
View ProjectSyncIt
March 16, 2016 – August 15, 2017
Google Drive Synchronization Client for Public PCs
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards personal projects, indicating self-motivation and initiative. However, the projects are diverse and not exclusively focused on data science, which might require some alignment for a dedicated Data Scientist role. The experience level is 0, suggesting a junior profile, which might not align with a senior Data Scientist role without further development.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The psychometric test score is 0, providing no insights.