Detail-focused Data Analyst with knowledge in data warehousing, process validation and business needs analysis. Proven to understand customer requirements and translate into actionable project plans. Dedicated and hard-working with passion for Big Data.
To seek and maintain full-time position that offers professional challenges utilizing interpersonal skills, excellent time management and problem-solving skills.
GPA: 6.37/10
Details : My project included the user registration and how the cellular mobile companies register ,allot number, payment of bill,check status of customer. I was awarded with 2nd best project in 12th class
Tools : Used Advanced Java programming and with the use of Netbeans IDE
Details : Controlled the back end of how the flight entertainment system and cabin crew touch panel which controls the cabin of flight.
Used java programming and unix for establishing connection between the package(which included all the codes) and the DSU server.
Tools : DSU(server), TPMU- touch passenger multimedia unit: which controlled the screen present at the back of each seat for entertainment purpose. , SVDU- smart
video display unit: which displayed the contents which were included in the programming for ex: Movies, games, songs, etc, ICMT- Interactive cabin management
terminal: can only be used by cabin crews to control the cabin systems.
Year : 2020
Details : This paper presents a facial expression recognition system employing Bezier curves approximation technique.
The system is based on facial features extraction using the knowledge of the face geometry and approximated by 3rd order Bezier curves representing the relationship
between the motion of features and changes of expressions. For face detection, color segmentation based on the novel idea of fuzzy classification has been employed that manipulates ambiguity in colors.
From human face structure, we divide in 3 regions such as right eye, left eye and mouth areas from the face image.
Firstly, comes the face detection and then detection of the skin region.
We crop the facial skin region and connect the largest skin region to detect the skin surface of the human face.
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