Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Feature extraction involves feature detection, description and matching which is the baseline of many computer vision applications like content based image retrieval, image classification, image recognition, object detection etc. Features detected should have greater repeatability and should be able to derive descriptors out of it that are highly distinctive and robust to changes in scale, orientation, rotation, illumination etc. This paper provides an insight about the performance comparison of the long existing SIFT and SURF descriptors. The evaluation is carried out in an experimental setup of object category detection which uses a SVM classifier to detect the category. © BEIESP.

Department of Smart Computing

School of Information Technology and Engineering

Vellore Campus

Department of Information Technology

Department of Database Systems

School of Computer Science and Engineering

International Journal of Innovative Technology and Exploring Engineering

Performance comparison of various feature descriptors in object category detection application using SVM classifier

Convolutional Neural Networks (CNN) are playing a vital role nowadays in every aspect of computer vision applications. In this paper we have used the state of the art CNN in recognizing handwritten Tamil characters in offline mode. CNNs differ from traditional approach of Handwritten Tamil Character Recognition (HTCR) in extracting the features automatically. We have used an isolated handwritten Tamil character dataset developed by HP Labs India. We have developed a CNN model from scratch by training the model with the Tamil characters in offline mode and have achieved good recognition results on both the training and testing datasets. This work is an attempt to set a benchmark for offline HTCR using deep learning techniques. This work have produced a training accuracy of 95.16% which is far better compared to the traditional approaches. © 2019 The Authors

Department of Information Security

Fulltext

Journal of King Saud University - Computer and Information Sciences

Benchmarking on offline Handwritten Tamil Character Recognition using convolutional neural networks

VIT Unitversity

International Journal of Advanced Research in Computer Science

CONTENT BASED IMAGE RETRIEVAL USING HYBRID-SVM

Internet of Things (IoT) in healthcare has gained tremendous appreciation as it has already improved the lives of millions of people worldwide. With the use of sensing devices, collecting data from different environments, devices, and equipment is now possible and appropriate decisions can be taken. Collected data is transferred over the network or internet and is able to be stored on the cloud or physical servers for analysis and future references. IoT has revolutionized the healthcare such that patients can be treated and monitored at the comfort of their homes without visiting the hospital. © RJPT. All rights reserved.

Research Journal of Pharmacy and Technology

A Survey on Applications of Internet of Things in Healthcare Domain

International Journal of Advanced Research in Computer Science and Software Engineering

Enhancement of Efficient Image Searching by using Advance Hashing Method

Department of Electrical Engineering

School of Electrical Engineering

International Journal of Computer Trends and Technology

Survey on IOT based Smart City

Programming improvement of portable applications includes a dynamic situation with every now and again evolving advances, client needs and limitations which requires progressed methodologies and systems in programming building. Versatile applications are created for different purposes in various classifications. This paper talks about the difficulties confronted in programming designing for portable applications, particularly for a science instructive and outreach point as respects innovations and procedures that could be utilized to investigate the maximum capacity of portability. Specifically, this paper examinations the fundamental difficulties that effect advancement in this field, for example, managing organizing conventions, upgraded network and the divided biological system of versatile stages. © IAEME Publication.

World University root node

International Journal of Civil Engineering and Technology

Software management issues in mobile application development