Sunil Malviya
@sirtbhopal.ac.in
Assistant Professor in Computer Science and Information Technology department
Sagar Institute of Research and Technology Bhopal
EDUCATION
B.E., M.Tech
RESEARCH, TEACHING, or OTHER INTERESTS
Human-Computer Interaction, Artificial Intelligence
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Arun Kumar Jhapate, Sunil Malviya, and Monika Jhapate
IEEE
Suspicious behavior is dangerous in public areas that may cause heavy causalities. There are various systems developed on the basis of video frame acquisition where motion or pedestrian detection occur but those systems are not intelligent enough to identify the unusual activities even at real time. It is required to recognized scamper situation at real time from video surveillance for quick and immediate management before any casualties. Proposed system focuses on recognizing suspicious activities and target to achieve a technique which is able to detect suspicious activity automatically using computer vision. Here system uses OpenCV library for classifying different kind of actions at real time. The motion influence map has been used to represent the motion analysis that frequently changes the position from one place to another. System uses pixel level presentation for making it easy to understand or identify the actual situation.
Sunil Malviya, Arun Kumar Jhapate, Ruchi Thakur, and Vipin Tiwari
IEEE
Sentiment Analysis is that the application of linguistic communication process, linguistics and text process. Sentiment Analysis is the opinion mining task that aims to obtain the writer's or speaker's feelings (“smile”, “anger”, “sorrow”, etc.), attitude (Positive, negative or neutral) towards particular task such as product reviews, movie reviews or overall tonality of document. It is one of the serious issues which can be solved by using Natural Language Processing (NLP) methods and so called text pre-processing. In this paper, focuses on to investigate the classifier to improve the classification process and what kind of NLP methods can be processed. There is a great deal of significant information on Internet that, really, is difficult to utilize. Procedure this information can enable to foresee future items, economy patterns or social certainties by preparing the individuals emotions that are shared on web. In this paper, proposed a hybrid model named DeLC model.
Farheen Ali, Sunil Malviya, and Neelesh Gupta
IEEE
This paper presents the Delayed least mean square (D-LMS) adaptive filter for deriving its Architectures for low complexity and high-speed implementation. Among many adaptive filter algorithms that exist in the open journals, this approaches which are derived from the minimization of the mean squared error between the output of the adaptive filter and some preferred signal seems to be the most well-liked. Probably the easiest algorithm belonging to this section is the Least Mean Squared (LMS) algorithm which has the advantage of low complexity and simplicity of implementation. It's a broadly used adaptive algorithzm for its low hardware complexity and robustness. Although in practical applications, several modified LMS algorithm had be proposed. Delayed LMS algorithm is suited in hardware implementation. An efficient architecture for the implementation of a delayed least mean square adaptive filter for achieving area delay power efficient and lower adaptation delay implementation, proposed methodology is of a novel partial product generator and a approach for optimized balanced pipelining across the time-consuming combinational blocks of the structure. The migration of DSP adaptive filter to RTL makes the algorithm much faster.