Notice Board :

Call for Paper
Vol. 5 Issue 9

Submission Start Date:
September 01, 2019

Acceptence Notification Start:
September 10, 2019

Submission End:
September 15, 2019

Final MenuScript Due:
September 25, 2019

Publication Date:
September 30, 2019


                         Notice Board: Call for PaperVol. 5 Issue 9      Submission Start Date: September 01, 2019      Acceptence Notification Start: September 10, 2019      Submission End: September 15, 2019      Final MenuScript Due: September 25, 2019      Publication Date: September 30, 2019




Volume II Issue III

Author Name
Pooja Trivedi, Dr. Bhupesh Gour
Year Of Publication
2016
Volume and Issue
Volume 2 Issue 3
Abstract
In current years, there has been an growing stipulate for computerized visual surveillance systems additional and further surveillance cameras are used in public Domain this is an ambitious aim which has attracted an growing amount of researchers to resolve frequently encounter surveillance problems of object detection, object tracking, object classification, and aberration detection over in the video attracting extensive interest due to public security. In this research, we proposed attempt to mine semantic context information together with object-specific circumstance information and scene-specific context information. On the other hand, video retrieval allow the customer to search for meticulous video segment based on some description commercial increase and SVM are included for feature selection and ensemble classification. Other researchers have studied optimization of support vector machine using genetic algorithms based on fuzzy logic through feature subset and b
PaperID
2016/IJRRETAS/4/2016/5610

Author Name
Harsha A. Chaudhari, Prof. Chhaya Nayak
Year Of Publication
2016
Volume and Issue
Volume 2 Issue 3
Abstract
In the recent year, the privacy takes major role to secure the data from various potential attackers. While publishing collaborative data to multiple data provider’s two types of problem arises, first is outsider attack and second is insider attack. Outsider attack is by the people who are not data providers and insider attack is by colluding data provider who may use their own data records to understand the data records shared by other data providers. In the proposed approach problem can be resolved by using different approaches as m-privacy, which is a technique which guarantees that the anonymized data satisfies a given privacy constraint against any group of up to m-colluding dataproviders. Second, Heuristic algorithms is also exploiting the equivalence group monotonicity of privacy constraints and adaptive ordering techniques for efficiently checking m-privacy given a set of records. Data provider aware anonymization algorithm with adaptive m- privacy checking stra
PaperID
2016/IJRRETAS/4/2016/4610