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

Department of Multimedia

School of Design

Vellore Campus

The Journal of Supercomputing

Stealth assessment strategy in distributed systems using optimal deep learning with game based learning

The recommender systems are used to mainly suggest recommendations to the online users by utilizing the user preferences recorded during the item purchase. No matter how, the performance of the recommendation quality seems to be inevitable and far satisfactory. In this paper, a new approach based on the mathematical model, Formal Concept Analysis (FCA) is used to improve the rating prediction of the unknown users which can certainly overcome the issues of the existing approaches like data sparsity, high dimensionality of data, performance of the recommendation generated for top n recommendation. The FCA method is applied using Boolean Matrix Factorization (ie. optimal formal concepts) in predicting the rating of the unknown users in the available user-item interaction matrix which proves to be more efficient in tackling the problem of computational complexity managing the high dimensionality of data. The proposed method is applied using item-based collaborative filtering technique and the experiment is conducted on the Movielens dataset which shows the satisfactory results. The experiments results are evaluated using the related error metrics and performance metrics. The experimental results are also compared with existing item-based Collaborative Filtering techniques which demonstrate that the performance of recommendation quality gradually improved with state-of-the-art existing techniques. Copyright © 2020 Chemmalar Selvi G. et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

World University root node

Fulltext

EAI Endorsed Transactions on Energy Web

Rating Prediction Method for Item-Based Collaborative Filtering Recommender Systems Using Formal Concept Analysis

Object detection is most required task in computer vision to meet the requirement of autonomous processes. The key challenge in object detection is to separate the foreground known as dominant information of the image from background. In this paper, a new model Squeeze and Excitation Region-Convolutional Neural Network (SER-CNN) is proposed which combines a Squeeze and Excitation (SE) embedded CNN with a Region proposal CNN (R-CNN) to detect salient objects. In SER-CNN, SE blocks are embedded in CNN and this extracts features made up of grand pixels which are accompanied with channel information. R-CNN generates salient map by fusing grand pixels with bounding box techniques to detect objects which is similar to the ground truth. DUT-OMRON, Pascal VOC and SOD dataset applied to find the performance of the SER-CNN. MAE and maxF performance evaluation measures are used for comparing the proposed work with the existing ones. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Department of Software and Systems Engineering

School of Information Technology and Engineering

International Journal of Speech Technology

Salient object detection based on adaptive recalibration technique through deep network

Magnetic resonance imaging (MRI) images are frequently sensitive to certain types of noises and artifacts. The denoising of MRI images is essential for improving visual quality and reliability of the quantitative analysis of diagnosis and treatment. In this article, a new block difference-based filtering method is proposed to denoise the MRI images. First, the normal MRI image is degraded by a certain percentage of noise. The block difference between the intensity of the normal and noisy MRI is computed, and then it is compared with the intensity of the blocks of the normal MRI image. Based on the comparison, the pixel weights are updated to each block of the denoised MRI image. Observational results are brought out on the BrainWeb and BraTS datasets and evaluated by performance metrics such as peak signal-to-noise ratio, structural similarity index measures, universal quality index, and root mean square error. The proposed method outperforms the existing denoising filtering techniques. © 2019 Wiley Periodicals, Inc.

VIT Unitversity

International Journal of Imaging Systems and Technology

Removal of noise in MRI images using a block difference‐based filtering approach

Journal of the Social Sciences

Widow Remarriage – A Stigma Even in Twenty First Century

It is reported that a novel third order organic nonlinear optical material namely, Pyrrolidin-1-ium 2-chloro-4-nitrobenzoate 2-chloro-4-nitrobenzoic acid (PCNCN) has been synthesized and grown by isothermal solvent evaporation solution growth technique. Single crystal X-ray diffraction analysis revealed that PCNCN belonged to monoclinic crystal system with a centrosymmetric space group of P21/c. The morphology of the as grown PCNCN crystal compared well with that obtained by theoretically generated morphology. The molecular vibrations of PCNCN were analyzed through Fourier transform infrared and NMR spectrum analyses. Optical properties such as transmittance, photoluminescence, and laser damage threshold were studied. The thermal stability of PCNCN was measured through TG-DTA measurement. The dielectric properties such as dielectric constant, dielectric loss, ac conductivity and activation energy of PCNCN single crystal were studied as a function of frequency at different temperatures. The PCNCN single crystals were further characterized for their third order nonlinear optical properties such as nonlinear absorption coefficient, nonlinear refractive index and optical limiting behavior using continuous wave Nd: YAG laser. The quantum chemical investigations were performed using B3LYP/6-311++G(d, p) basis set. © 2019 Elsevier Ltd

Physics

School of Advanced Sciences

Chennai Campus

Optics & Laser Technology

Synthesis, structural, dielectric, laser damage threshold, third order nonlinear optical and quantum chemical investigations on a novel organic crystalline material: Pyrrolidin-1-ium 2-chloro-4-nitrobenzoate 2-chloro-4-nitrobenzoic acid for opto-electronic applications

In spite of other media industries such as Radio, Print and Television adapted to using digital technologies, the cinema industry stuck in celluloid medium itself until second decade of 21st century until the computational power got increased exponentially. Though the digital use started in 1990s it took three decades for the Industry to completely adapt to digital medium. The celluloid medium acted as barrier for experimenting different content due to its nature that demands heavy expenses, complicated workflow and man power. Digital technologies opened up the barriers laid by celluloid technology thus expanded the horizons for creative experiments and an invitation for new entrants due to its user friendly simplicity in nature. Twenty first century fosters the Indie film movement where many young minds are encouraged to get into movie making with cheaper digital tools that are available. The blockbuster success and critically acclaimed six Telugu debut talents movies that were released in the year 2019 cite an example of how the film industry is getting changed towards ease and lighter way. Many indie movies started coming out with fresh approaches in the content and structure. A sneak preview of OTT platforms like Amazon Prime, Netflix, YouTube Channels and a host of other online video platforms is a standing testimony for democratization of creativity in the field of cinema. Entry of corporate firms and the new promising technologies the industry is getting more opportunities to their wings on different app based viewing platforms. The new opportunities also throw challenges in quality contents of cinema. Since the technology is easily available at less cost people with narrow filthy ideas can enter the industry and easily disseminate their irrelevant bad contents. There are threats on spoiling narrative context of film without an inherent perils of the story. This study aims at exploring the unconventional cinema content that are experimented by new entrants in the cinema industry. The two variables, Celluloid and Digital have been taken for analysis. Dr. Valarmathi Subramaniam "Content Evolution in South Indian Cinema Mediated by Digital Technologies of 21st Century" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31764.pdf Paper Url :https://www.ijtsrd.com/humanities-and-the-arts/journalism/31764/content-evolution-in-south-indian-cinema-mediated-by-digital-technologies-of-21st-century/dr-valarmathi-subramaniam

International Journal of Trend in Scientific Research and Development

Content Evolution in South Indian Cinema Mediated by Digital Technologies of 21st Century

Background: The proposed work uses two approaches as its background. They are (i) LBP approach (ii) Kirsch compass mask. Texture classification plays a vital role in object discrimination from the original image. LBP is majorly used for classifying texture. Many filtering based methods co-occurrence matrix method, etc., were used, but due to the computational efficiency and invariance to monotonic grey level changes, LBP is adopted majorly. Second, as Edge plays a vital role in discriminating the object visually, Kirsch compass mask was applied to obtain maximum edge strength in 8 compass directions which has the advantage of changing the mask according to users own requirement than any other compass mask. Objective: The objective of our work was to extract better features and model a classifier for the Multimedia Event Detection task. Methods: The proposed work consists of two steps for feature extraction. Initially, an LBP based approach is used for object discrimination, later, convolution is used for object magnitude determination using Kirsch Compass mask. Eigenvalue decomposition is adopted for feature representation. Finally, a classifier is modelled using a chi-square kernel for the event classification task. Result: The proposed event detection work is experimented using Columbia Consumer Video (CCV) dataset. It contains 20 event based videos. The proposed work is evaluated with other existing works using mean Average Precision (mAP). Several experiments have been carried out to evaluate our work, they are LBP vs. non-LBP approach, Kirsch vs. Robinson compass mask, Kirsch masks angle wise analysis, comparison of above approaches are performed in a modeled classifier. Two approaches are used to compare the proposed work with other existing works.They are (i) Non Clustered Events (events were considered individually and one versus one strategy was followed) (ii) Clustered Events (some events were clustered and followed one vs. all strategy and remaining events were non-clustered). Conclusion: In the proposed work, a method for event detection is described. Feature extraction is performed using LBP based approach and Kirsch compass mask for convolution. For event detection, a classifier model is generated using the chi-square kernel. The accuracy of event classification is further increased using clustered events approach. The proposed work is compared with various state-of-the-art methods and proved that the proposed work obtained outstanding performance. © 2020 Bentham Science Publishers.

Recent Advances in Computer Science and Communications

A framework for multimedia event classification with convoluted texture feature

Video stitching enables creation of videos with a wide field of view from videos captured from ordinary, probably moderately displaced, cameras. In this paper, a novel video stitching algorithm based on multi-view feature detection and registration using region-based statistics has been proposed. While stitching the videos captured using moving cameras, the motion in those cameras will affect the alignment of video frames. Movements in the cameras and in the objects will affect the temporal consistency while stitching the videos. Temporally reliable feature points are considered to maintain both spatial and temporal consistency using multi-view spatiotemporal feature points in this paper. Experiments have been carried out on different data sets, and the results showed the better and effective performance of the proposed approach. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

Visual Computer

Video stitching based on multi-view spatiotemporal feature points and grid-based matching

Human activity recognition is an active and interesting field in computer vision from past decades. The objective of the system is to identify human activities using different sensors such as cameras, wearable devices, motion and location sensors, and smartphones. The human actions are automatically identified through their physical activities in human–computer interaction. Determining the human action in an uncontrolled environment is a challenging task in human activity recognition system. In this paper, a novel approach is proposed to recognize human actions effectively in an uncontrolled environment. A frame for the video segment is selected by temporal superpixel, which acts as the input image for the model. Convolutional neural network techniques are applied to extract the features and recognize the human activities from the image. The proposed method has experimented on KTH database and it shows the performance of the method in terms of accuracy. However, the proposed method has attained better accuracy when compared to the existing methods. © 2020, Springer Nature Singapore Pte Ltd.