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Cse final year projects are similar to all degree Bsc, Msc, BCA, MCA, B.Tech/M.Tech and MS students. We offer cse final year projects to convert theoretical knowledge into practical implementation knowledge. We support computer science projects with various domains as machine learning, augmented reality, networking, context aware computing, bio medical, software maintenance and mobile computing. We develop recent computer technology for computer science students and implemented in java, .net and android. We efficiently implement various types of open source and simulation tool to model and simulate computer domains.
We develop advance biometric projects from Elsevier to investigate various biometric sources and sensor source with bio metric technology. We adopt various bio metric sources as fingerprint, finger veins, gait, face and iris. We implement new algorithm to recognize biometric source information.
We implement medical application which needs efficient algorithm to design, implement and experiment medical images during the process of object sharpening, field covering, object selection, image segmentation and partition various number of geometric optimization problem may occur. We develop CSE final year projects to investigate the optimization problem in medical image application.
CSE FINAL YEAR Projects
Automatic emotion detection:
We establish computer science projects to create a computer machine as human computer which understand the human emotion. Our main aspect of automatic emotion detection projects is automatically sense human reaction by extracting body movements, speech contour, and physiological response and interaction patterns. We require computer interface application to provide effective and user friendly way for automatic emotion detection system.
We define grid as a large computing framework with various resources. We share resources among various serves to effectively process user task. We execute millions of jobs in grid computing framework and in turn it have possible to occur multiple number of failure jobs. We evolve machine learning a data mining approach to analyze workload, power factor and capacity of grid computing server. We effectively deploy this algorithm in grid to decrease the job failure numbers.
We deploy scheduling algorithm in all computing environment which perform an overall control of task execution. We adopt energy and power aware scheduling algorithm to minimize power and energy consumption in real time system. We developed more than 90+ projects in computer science to reduce energy consumption as voltage scaling, sleep mode control and frequency scaling.
We implement social & health network with rich source confidential information to preserve health and personal information of patient and social network user. We develop privacy preserving projects with security mechanism to satisfy user needs.