Prof. Varsha Hemant Patil
@engg.matoshri.edu.in
Professor & Head, Department of Computer Engineering
Matoshri College of Engineering and Research Centre, Nashik
Professor Dr. V. H. Patil is currently working as Professor & Head of Computer Engineering department with additional responsibility of Vice-principal at Matoshri College of Engineering & Research Centre situated at Nashik. She is currently Chairman of Board of Studies,Computer Engineering at Savitribai Phule Pune University. She has earlier extended her expertise as member of Board of studies and member of various bodies at Computer and IT Engineering at SPPU as well as other universities. She is recipient of various honors & awards. To name few:“Best Teacher Award”, Savitribai Phule Pune University ,“Women ICON of Nashik”, Sakal Group, Nashik,“Significant Contribution Award”, Computer Society of India, A state level Engineering Teacher Award, Engineering Foundation, Maharashtra , Recipient of “Engineering Achievement Award” from Institution Engineers . She has authored 3 books in areas Discrete Mathematics, Data Structures and Theory of Computation published by renowned publishers as
EDUCATION
PhD, ME. BE Computer Engineering
RESEARCH INTERESTS
Parallel Computing, Soft Computing, Image Processing, and Graph Processing.
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Swati A. Bhavsar, Varsha H. Patil, and Aboli H. Patil
Springer Science and Business Media LLC
Namrata G Kharate and Varsha H Patil
Institute of Advanced Engineering and Science
Machine translation is important application in natural language processing. Machine translation means translation from source language to target language to save the meaning of the sentence. A large amount of research is going on in the area of machine translation. However, research with machine translation remains highly localized to the particular source and target languages as they differ syntactically and morphologically. Appropriate inflections result correct translation. This paper elaborates the rules for inflecting the parts-of-speech and implements the inflection for Marathi to English translation. The inflection of nouns, pronouns, verbs, adjectives are carried out on the basis of semantics of the sentence. The results are discussed with examples.
Geetanjali Kale, Varsha Patil, and Mousami Munot
Springer Science and Business Media LLC
Namrata G. Kharate and Varsha H. Patil
Springer Singapore
Ranjit M. Gwande and Varsha H. Patil
Springer Singapore
Varsha H. Patil, Swati A. Bhavsar, and Aboli H. Patil
IOS Press
Swati K. Bhavsar and Varsha H. Patil
Springer International Publishing
Rahul L. Paikrao and Varsha H. Patil
IEEE
Cloud is a modern day paradigm mainly focusing on the remote resource sharing for the economical computing. Cloud provides various service models and tries to help the customer for better resource management. Due to remote resource sharing few security concerns arise which need to be handled in very systematic way. In this paper we have tried to survey and analyze various security issues arising due to different aspects of cloud computing. We second the thoughts put by various researchers and categorize them broadly like issues identified by CSA, issues identified due to location of the data, issues inherited from networking and more importantly the issues raised due to vulnerabilities in virtualization. Hypervisor vulnerabilities are area of concern as far as VM management is concerned. A security as a service model is proposed for Virtualization Vulnerabilities.
Geetanjali Vinayak Kale and Varsha Hemant Patil
IGI Global
Vision based human motion recognition has fascinated many researchers due to its critical challenges and a variety of applications. The applications range from simple gesture recognition to complicated behaviour understanding in surveillance system. This leads to major development in the techniques related to human motion representation and recognition. This paper discusses applications, general framework of human motion recognition, and the details of each of its components. The paper emphasizes on human motion representation and the recognition methods along with their advantages and disadvantages. This study also discusses the selected literature, popular datasets, and concludes with the challenges in the domain along with a future direction. The human motion recognition domain has been active for more than two decades, and has provided a large amount of literature. A bird's eye view for new researchers in the domain is presented in the paper.
Snehal Mohan Kamalapur and Varsha Patil
IGI Global
The issue of parameter setting of an algorithm is one of the most promising areas of research. Particle Swarm Optimization (PSO) is population based method. The performance of PSO is sensitive to the parameter settings. In the literature of evolutionary computation there are two types of parameter settings - parameter tuning and parameter control. Static parameter tuning may lead to poor performance as optimal values of parameters may be different at different stages of run. This leads to parameter control. This chapter has two-fold objectives to provide a comprehensive discussion on parameter settings and on parameter settings of PSO. The objectives are to study parameter tuning and control, to get the insight of PSO and impact of parameters settings for particles of PSO.
Geetanjali Vinayak Kale and Varsha Hemant Patil
IGI Global
Vision based human motion recognition has fascinated many researchers due to its critical challenges and a variety of applications. The applications range from simple gesture recognition to complicated behaviour understanding in surveillance system. This leads to major development in the techniques related to human motion representation and recognition. This paper discusses applications, general framework of human motion recognition, and the details of each of its components. The paper emphasizes on human motion representation and the recognition methods along with their advantages and disadvantages. This study also discusses the selected literature, popular datasets, and concludes with the challenges in the domain along with a future direction. The human motion recognition domain has been active for more than two decades, and has provided a large amount of literature. A bird's eye view for new researchers in the domain is presented in the paper.
Geetanjali Kale and Varsha Patil
IEEE
Human motion recognition is a challenging problem having applications in multifaceted domain. It has significance in sports, surveillance, human-computer interaction etc. Proposed Bharatna̅ yam Adavu Recognition System from Depth Data (BARSDD) recognizes the Adavu in Bharatna̅ yam using extended state model. Bharatna̅ yam is one of the Indian traditional dance forms. A specific sequence of poses in Bharatna̅ yam is known as Adavu. Bharatna̅ yam dances are based on stories of Rama̅yana and Maha̅bha̅rata, the Indian Epics. Only, expert can understand this sentiment (bha̅va) and posture (mudra̅). Main objective behind this work is that BARSDD system should recognize meaning of dance and display it for audience. We have represented Adavu using extended state model. Five basic Adavu Tatta, Natta, Sarikal, Visharu, and Kuditta̅metta̅ are considered for recognition. Kinect sensor is used to achieve more reliable, accurate and cost-effective depth image sequence. Contour features extracted using Canny Edge Detection algorithm are used for representation of dancer's posture. Freeman Chain Code Algorithm followed by compression using run length encoding is applied to store contours. System is tested for all five Adavu performed five times each. Our system shows average 78.38% recognition rate. It is observed that failure of recognition is due to non-identification of some intermediate posture in Adavu.
Snehal Mohan Kamalapur and Varsha Hemant Patil
IEEE
Particle Swarm Optimization is motivated by collective behavior in the nature. Earlier PSO variants were biased and rotationally variant because of dimension by dimension method. Clerc proposed Standard PSO 2011 version to overcome the bias which modifies velocity in a geometrical way. Particle Swarm Optimization is an optimization technique having few parameters to tune. The neighborhood topology and acceleration coefficients are two major parameters to enhance PSO performance. The work under consideration extends the existing parameter setting techniques on acceleration coefficients. The concept of a "dynamic" neighborhood is explored here. The paper focuses on random and linear increment and decrement acceleration coefficients as well as random neighborhood topology link based variants. Experiments are conducted on benchmark functions to evaluate the performance.
Deepali Sale, Varsha Patil, and Madhuri A. Joshi
IEEE
Image fusion plays an important role in image enhancement and retrieval. For multi-focus image fusion as it is related to frequency distortion the wavelet with symmetric property is more useful to retrieve the image. Hence, to select the wavelet family, which provides better frequency resolution is of immense importance. Due to this property of haar and biorthogonal wavelet bases, they are used for multi focus image fusion. Spatial frequency measures the overall activity level in an image. Some abrupt spatial changes in the image are represented by the high spatial frequencies in the image like edges. Edges are the salient features of an image which gives the information about the fine details. Low spatial frequencies, on the other hand, represents global information about the shape and the orientation of an image. Due to this spatial frequency is used as the feature of selection. A novel hybrid approach to multi-focus image fusion is used. Wavelet coefficients of both the source images are combined by applying different fusion rules for low and high frequency coefficients. Applied a Laplacian pyramid based transform onto the low frequency coefficients of both the input images. For coefficient selection applied a maximum selection fusion rule. High frequency coefficients are selected based upon maximum spatial frequency. The presented algorithm is compared with those of the individual fusion methods. The better result obtained with the combined method (proposed) as compared to the individual methods. The statistical analysis is performed using reference and non reference based metrics. Important feature based metrics are considered.
Geetanjali Kale and Varsha Patil
Springer Berlin Heidelberg
Mininath K. Nighot, Varsha H. Patil, and G.S. Mani
IEEE
This paper reports studies carried out on a multi-robot system assigned with the task of hunting down a rogue element in its vicinity whose location is not known. Swarm Intelligence (SI) has been used in the studies for organizing the multi-robot coordinated strategy to capture/enclose the target/invader. MATLAB based simulation has been used to ascertain the Flexibility, Robustness and Self-organization capability of the SI based strategy.
Sayali Charhate, Anurag Dani, Rekha Sugandhi, and Varsha Patil
IEEE
Natural language processing applications invariably perform word sense disambiguation as one of its processing steps. The accuracy of sense disambiguation depends upon an efficient algorithm as well as a reliable knowledge-base in the form of annotated corpus and/or dictionaries in machine readable form. Algorithms working on corpus for sense disambiguation are generally employed as supervised machine learning systems. But such systems need ample training on the corpus before being applied on the actual data set. This paper discusses an unsupervised approach of a graph-based technique that solely works on a machine-readable dictionary as the knowledge source. This approach can improve the bottleneck problem that persists in corpus-based word sense disambiguation. The method described here attempts to make the algorithm more intelligent by considering various WordNet semantic relations and auto-filtration of content words before graph generation.
Snehal Mohan Kamalapur and Varsha Hemant Patil
IEEE
Particle swarm optimization (PSO) is motivated by the social behavior of individual in a group. The trajectory of the particles in PSO show that a particle catches a wave during the search. This paper analyzes the trajectory of a particle in PSO with and without construction coefficient. The particles follow the path defined by sinusoidal wave while amplitude and frequency are random. The paper considers multidimensional and multi particle swarm. The paper provides a derivation of the closed from of PSO with constriction coefficient.
Varsha H. Patil, Datttraya S. Bormane, and Vaishalee S. Pawar
IEEE
Super resolution imaging refers to inferring the missing high resolution image from low resolution image(s). Super resolution methods are generally classified into reconstruction based and learning based methods. The learning based methods fully learn the intensity prior between all bands of images. For most of these, some fake information can be inevitably introduced into synthesized high resolution image though the image may offer visually good effects. For medical image analysis, it might deteriorate the image analysis and diagnosis performance. In this paper we propose a better learning using real image training set that enhances the high frequency information. The method exploits richness of real-world images. The training set is preprocessed images so as to extract the structural correlation. The technique learns the fine details that correspond to different image structures seen at a low-resolution and then uses those learned relationships to predict fine details in other images.
M. Venu Gopala Rao and S. Vathsal
IEEE
The super-resolution algorithm constructs high resolution image using low resolution images. The ideal algorithm should be fast, and should add sharpness and detail, both at edges and in regions without adding artifacts. In this paper we propose a technique to yield a color super resolved image from four low resolution color images. We distinguish two major phases: registration and interpolation. Existing registration techniques are computationally time consuming. Current interpolation methods introduce blocking artifacts and also smoothens the edges and is unable to restore high frequency details in image. We propose efficient registration and wavelet based interpolation for SR image reconstruction. Our technique is efficient and computationally fast having clear perspective of real time implementation. PSNR obtained and objective test results presented in paper support our claim.
RECENT SCHOLAR PUBLICATIONS
MOST CITED SCHOLAR PUBLICATIONS
Publications
• Paikrao, R.L., Patil, V.H. , “Security as a Service Model for Virtualization Vulnerabilities in Cloud Computing”, 2018, pp. 559–562, 8529573
• Gawande, R.M., Patil, V.H , “A Comprehensive Review on Machine Learning Approaches for Prediction of Gestational Diabetes Mellitus”, Springer, First Doctoral Symposium, in Networks and Systems 2021, 169 LNNS, pp. 475–484
• Mrs. Snehal M. Kamalapur & Dr. Varsha H. Patil, “Impact of Acceleration Coefficients and Random Neighborhood Topology Modification Threshold on SPSO”, First International Conference on Computing, Communication, Control And Automation (IEEE), 26th & 27th Feb 2015, ISBN: 978-1-4799-6892-3
• Mrs. Geetanjali Vinayak Kale & Dr. Varsha Hemant Patil, “Bharatnatyam Adavu Recognition From Depth Data”, Third International Conference on Image Information Processing (IEEE), 25th Feb. 2016, DOI 10.1109/
• V. H. Patil, D. S. Bormane and H. K. Patil, “Color Super Resolution Image Reconstruction”, International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 2007, ,13-15 Dec 2007, IEEE COMPUTER SOCIETY,PP-366-370 ISBN: 0-7695-3050-8
• Mrs. Dhole S.A. & Dr. Prof. Patil V.H, “ Performance Comparison of face Recgnition using PCA,DWT &Gaborbank Features, 3rd International Conference on Recent Trends in Engineering & Technology ICRTET, Vol. 3, March 2014
• V. H. Patil and D.S. Bormane, “Super Resolution for Network Aware Appli
GRANT DETAILS
• Completed Minor Research project as principal investigator titled “Technique for Reconstructing Super Resolution Image using Low Resolution Natural Color Image” under research grant from SPPU, BCUD/578 -2006-08
• Completed Minor Research project as principal investigator “Use of Wireless Sensor Network and GPRS Module for Automated Irrigation System”, under research grant of SPPU, BCUD/83 dt-09/03/2014 Grant No: 14ENG000850, 2014-2016.
• Completed Minor Research project as co- investigator “Vision Based Human Motion Recognition and Analysis in Indoor Scene for Activity Monitoring using Distributed Data Capture”, SPPU, Grant No:14ENG002310, 2015-2017
• Completed Minor Research project as co- investigator “Marathi Handwritten Character Recognition System using Neural Networks”, Savitribai Phule Pune University Grant No:14ENG001284, 2016-2018.
RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)
Patents:
1. Filed Patent “IoT Based Pest Detection System Inside Fruits and Vegetables”, Status- Published, Application No. 201921005563.
2. Filed patent “System And Method For Motion Analysis And Feedback For Amendment Of Human Action”, Status-Published, Application No. 201621029482.
3. Filed Patent “IoT Based System For Computing Human Density For Critical Situation Recognition And Precaution For Avoiding Accidents”, Status: Published, Application .
Copyrights:
1. Registered copyright for “Sparse Matrix and Its Efficient Representation “, Registration Number: L-72345/2018,
2. Registered copyright for “A Novel Technique for Reconstruction of Super Resolution Image Reconstruction Using Natural Low Resolution Color Image “, Registration Number-L-70635/2017
3. Registered copyright for “Questionnaire For Study and Analysis of Impact of stress On Health of Employee”, Registration Number L-75629/2018,
4. Registered copyright for “The Movie PINK- A message for Society My Opinion “, Registration Number-L-71808/2018
5. Registered copyright for “Research Scholar Handbook “, Registration Number-L-71157/2017
6. Registered copyright for “Project Workbook”, Registration Number- L-66962/2017
7. Registered copyright for “Feature Inference Approach for Feature selection Using PSO”, Registration Number 54044/2014-CO/L
8. Registered Copyright for “Malware Detection Analysis and Classification of Malware on Android”, Registration Number L-66147/2017
9. Registered Copyright
Industry, Institute, or Organisation Collaboration
1. Served as Convener, member Program Committee, Reviewer and Session Chair for various National and International Journals and Conferences.
2. MIR Lab, NY: Association with Machine Intelligence Research Lab, NY as researchers. Instrumental in activities such as organization of symposiums, conferences and similar tasks.
3. Research Centers- Associated with research centers (PhD programme) for activities like- PhD students selection interviews, PhD Progress sessions/presentations, Thesis Evaluation as referee, Chairman and Examiner at PhD defense.
4. Inter-Academic Institute Association- Associated with various institutes such as Engineering, Management and Autonomous in capacity of member academic council, BoS, conducting guest lectures, member DAB (Department Advisory Board), member of Academic Audit and similar.
5.. Association with Open University YCMOU:
Association as Course Instructor for “IT for Managers” for MBA program
Association Regarding Examination Conduction
Association regarding curriculum design
Developed a Course Material for “Algorithms” for Engineering Course at WAWASAN Open University, Malaysia, July 2007.
3. Association with Affiliated University-Savitribai Phule Pune University (SPPU)-