Zoha Fatima
FAST
· 2022
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I18 - 0565
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Academic
Program
BSCS
CGPA
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Year
2022
Education
SEECS
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DOB
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Career
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Target role
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Skills
Python, Pytorch, MySQL, JavaScript, AJAX, JQuery, Bootstrap, PHP, Visual Studio, PyCharm, Jupyter, Deep Learning, YOLOV5
Verbatim text
The exact text the LLM saw on the page (or the booklet text from the old import).
This is what powers semantic search.
WicketToWicket WicketToWicket is an AI empowered customized-cricket-highlights-generating and analysis platform. Our product aims to improve an individual player performance as well as collective strategies of teams, and facilitates critical decisions in the game of cricket by revolutionizing traditional cricket coaching and analysis methods while making them robust through Deep Learning techniques. Our application primarily uses YOLOV5 Deep Learning architecture to classify a particular frame of pitch that corresponds to the start of a bowling delivery, then labels the trimmed bowls with bowl by bowl commentary and match summary, and performs further analysis based on these results. The scope of our project is Pakistan Super League specifically its 6th edition. Features include: Cricket Highlights on Demand Player Coaching Team (i.e. Playing Eleven) Selector Technology Used: Python, Pytorch, MySQL, JavaScript, AJAX, JQuery, Bootstrap, PHP, Visual Studio, PyCharm, Jupyter Supervisor Name: Mr. Syed Muhammad H. Mustafa Group Members: Zoha Fatima (I18 - 0565) Abdullah Ansar (I18 - 0446) Saram Atif (I18 - 0659)
Provenance
Source file: Graduate Directory FAST School of Computing 2022 Final Version (07-06-2022).pdfFrom job #25 page 272
Created: 1778226154