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Dr. Parul Jadhav

Associate Professor

School Of Electronics & Communication

MIT World Peace University, Pune. India.


With over 29 years of diverse academic experience, she has been one of the pioneering members of ECE department. Her areas of interest involve Advanced Signal Processing, Video analytics, Video compression,  Embedded Systems, and Deep Learning.
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Dr. Parul Jadhav, is an Associate Professor in the school of Electronics and Communication at MIT WPU. She has over 29 years of experience in teaching, learning, research and administration, across diverse domains and technologies. Her areas of interest are in the field of signal processing, video analytics, Artificial Intelligence.


Ph.D (Electronics and Telecommunication)

COEP ( College Of Engineering Pune.

Her publications include over 30 papers in National and International Journals

Core areas in which research is carried out are

  • Video processing, adaptive video streaming

  • Compression techniques

  • Signal Processing

  • Machine Learning


First Class

ME (Electronics and Telecommunication)

CoEP ( College Of Engineering Pune. )


First Class with Distinction.

BE (Electronics and Telecommunication)

CoEP ( College Of Engineering Pune. )

Oct. 2019
Funding Received from Department of Science and Technology- Women Scientists Scheme (WOS-B)

New Research Grant : Funding Received from   Department of Science and Technology- Women Scientists Scheme (WOS-B)  for,  “ Yield Prediction and Quality Assessment of Grapes in Vineyard Using LiDAR Technology ”


Principal Investigator

Worked as Principal Investigator on the BCUD Funded project, “Implementation of Optimized Video Compression Standard for Real Time Application,” 2012-2014.

5th August 2010

“MAEER’s MIT Foundation Day Award”

Honoured with, “MAEER’s MIT Foundation Day Award”, as a token of appreciation of contribution to MIT through the noble profession of teaching on the occasion of 28th Foundation Day of MAEER’s MIT on 5th August 2010


Research Themes

Video Compression Techniques

Design of an Optimized Rate Control Technology for Scalable Video Coding:

This research is focused on optimizing video compression technique. The encoder/ decoder used for my research were based on H.264 video compression standard. The research lead to a new algorithm for bit rate control of various scaled video streams while maintaining the quality of the video to the acceptable limits. The specific steps include understanding of various video coding standards, their study, schemes adapted for coherency, gaps thereof, MPEG2/4 and H.264 architecture and focus on scalability schemes.


Research Contributions:

Development of spatial resolution based macro block mapping scheme for the enhancement layer which can assign lower macro block’s partition of the base layer to the enhancement layer.

Development of spatial-temporal search algorithm at the enhancement layer to increase the prediction accuracy and ultimately the coding efficiency.

Development of independent rate control algorithm to regulate the quantization parameter and ultimately the bits consumed per layer per frame for combined scalability

Video Analytics:

Video Analytic System for Public safety:


Normal and Abnormal human activity detection using deep learning models is a significant topic in computer vision. It will help in reducing increasing crime rate by preventing treacherous actions. There is huge advancement in human action recognitions and prediction related research but still state of art algorithms needs improvement in classifying it. This project focuses on Normal activity detection for humans. Main objective will be to propose a framework for analyzing human behavior. Here Convolutional neural Network will be used for Normal activity detection, followed by Recurrent Neural Networks (RNN) and long short term memory (LSTM ) to detect criminal actions. Model will be implemented for Indian crime scenarios also to detect criminal behavior. Transfer learning approach will be used to predict suspicious activity.

Signal Processing

Image Reconstruction Using Entropy Method :

Photons from various events in space reach the CZT Imager detector plate and form a “Coded-Mask Image”. The optimum performance of a coded-mask camera requires that every sky position is encoded on the detector in a unique way. This can be stated in terms of the autocorrelation function of the mask pattern. Our project aims at retrieving the contents of a cleaned FITS file containing this data and maximizing the entropy of the “energy” pattern of the photons incident on the detector to give us the most optimized estimate of the actual data.

Research Projects

Yield Prediction and Quality Assessment of Grapes in Vineyard Using LiDAR sensors and Image processing

Research funding by Department of Science and Technology, Government of India under Women Scientists Scheme (WOS-B) 


Grapes are one of the remunerative cash crops that improve the economy of farmer as well as country. To support the farmer, this research proposal incorporated vineyard management in particular to predict vineyard’s yield by using LiDAR as a tool during harvesting period where it is done manually today. To achieve the same, dataset of grape cluster with 2D and 3D cameras will be created. The methodology includes grape cluster detection, and area/volume estimation for yield prediction using Deep Learning technology.

Implementation of Optimized Video Compression Standard for Real Time Application

Research funding by Department of Science and Technology, Government of India under Women Scientists Scheme (WOS-B) 


Video data is encoded several number of times as per the specifications of end users decoding device. The main problem with this method is that it is difficult to adaptively stream non-scalable video contents to heterogeneous client terminals over time-varying communication channels. For non-scalable video data, the server may transcode the bit stream to reduce the bit rate, frame rate or spatial resolution. This project contributed in development of an algorithm to implement scalable video coding technique to adapt to varying availability of bandwidth.

Lidar Technology

Object Detection and Classification Using Sensor Fusion of Camera and Lidar:


The aim of sensor fusion is to use the advantages of each to precisely understand its environment. The camera is a very good tool for detecting roads, reading signs or recognizing a vehicle but fails to provide distance and struggles in low light conditions. The Lidar is better at accurately determining the position of the vehicle. This  project focuses on detecting, classifying and finding exact location of objects in a 3D space using Camera and LiDAR to aid self-driving vehicles. Carla simulator is used to provide all the necessary Camera and LIDAR data.

This work focuses on fusing of the data from both the sensors using Machine learning. We propose a novel approach to detect objects by first converting 3D space lidar data to 2D plane binary image and mapping of  centroids of the objects in lidar processed images and camera images

Research Supervision

PHD Graduates


Ms. Saylee Begumpure

Researcher in video analytics for human action detection

Ph.D.s Ongoing


Ms. Dhanashree Barbole

Researcher in Estimation techniques for crop yield using image analytics and machine learning

Savita Pawar.JPG

Savita Pawar

Researcher in Design of disease prediction system on Grape crop due to impact of climate change

Mandar Gholap.JPG

Mandar Kolap

Researcher in Performance Analysis of Wearable Reconfigurable MIMO Antenna for Biomedical Applications


Data Set:


  • S. Begumpure, Parul Jadhav, “Crime Video Dataset for Indian Scenario”,

Papers Published

  1. D. Barbole, P.Jadhav, “GrapesNet: Indian RGB and RGB-D Vineyard Image Dataset for Deep Learning Applications”, Data In Brief- Accepted- March 2023

  2. S. Muley, P. Jadhav, “Artificial Intelligence for the Detection of Covid-19 Pneumonia on Chest X-Ray,” 2022 IEEE 6th Conference on Information and Communication Technology (CICT-2022), 18-20 November 2022.

  3. A. Sutar, A. Kulkarni, A.Jain, P. Jadhav, V. Gohokar, “Physics Informed Neural Networks – A Methodology Review “, Computing, Communication, Control and Automation (ICCUBEA-2022), 26.27. Aug. Pune, India

  4. D.Barbole, P. Jadhav, “Grape Yield Prediction using Deep Learning Regression Model”, IEEE International Conference for Advancement in Technology, (ICONAT), 21-22 Jan. 2022, Goa, India, DOI:10.1109/ICONAT53423.2022.9726026

  5. S. Begumpure, P. Jadhav, “Intelligent video analytics for human action detection: a deep learning approach with transfer learning”,International Journal of Computing and Digital Systems, Vol 11, Issue 1, pg. 63-71, Jan 2022

  6. P. Chaudhary, R. Paranjape, N. Joshi, P. Jadhav, “An efficient system to quantify error in Sensor Fusion for Cameras in ADAS”, IEEE 2021 International Conference on Smart Generation Computing, Communication and Networking (SMARTGENCON)”. 28-29 Oct. 2021, Pune, Maharashtra, India

  7. D. Barbole, P. Jadhav, “ A Review on Fruit Detection and Segmentation Techniques in Agriculture Field,”International Conference on Image Processing and Capsule Networks, King Mongkut’s University of Technology Thonburi, Thailand, Dayeh University, Taiwan, and Tribhuvan University Nepal, Bangkok, Thailand, May 2021

  8. S. Begumpure,P. Jadhav, “Enhanced video analysis framework for action detection using deep learning”,International Journal of Next-Generation Computing, Vol 12, Issue2, pg. 218-227, April 2021

  9. S. Srivastav, Y. Chaudhary, Y. Damania, P. Jadhav, “Deep Learning Techniques for Automated Image Captioning”,Fifth International Conference on Smart Trends in Computing and Communications (SmartCom 2021),Las Vegas, Nevada, United States,April 2021

  10. D. Barbole, P. Jadhav, “Comparative Analysis of Deep Learning Architectures for Grape Cluster Instance Segmentation”, Journal of Information Technology in Industry, Vol 9, Issue 2, pg. 344-352, March 2021

  11. Y. Khare, A. Hundekari, P. JadhavA Comparative Review of Generic Object Detection Algorithms”, International Journal of Management, Technology And Engineering, Vol.11, Issue 3, pg. 204-214, March 2021

  12. D.Toshniwal, A. Patil, N.Vachhani, P. JadhavAI Coach for Badminton”,

  13. R.Tilawat, P. Sand, P. Ghadge, P. Jadhav “Applications of Computer Vision in Agriculture”, International Journal of Engineering Applied Science and Technology, Vol.5,Issue 9, pg. 166-168, Mar. 2021

  14. V. Dhopate, S. Panhalkar, S. Gangula, P.Jadhav “Vision Transformers: History, Significance, Applications and Furture Scope”, International Journal of Management Technology and Engineering, Volume XI, Issue 2, pg 79-90, Feb. 2021.

  15. S. Begumpure, P.M. Jadhav, “Enhanced video analytics for human action detection: a deep learning approach”, International  Virtual Conference on Recent Trends in Engineering and Technology VISHWACON 2020", Vishwakarma Institute of Information Technology ,Pune, Nov. 2020 

  16. A. Nahar, S. Shukla, P.M. Jadhav, “Iterative Deconvolution for Multidimensional Signals”, 2020 IEEE International Conference for Innovation in Technology (INOCON) Bangaluru, Nov 6-8, 2020

  17. S. Routray, A. John, A. Syed, P. M. Jadhav, “Inverse Kinematics Solution for a Robotic Arm Through Geometric and Iterative Fusion Based Modelling ”, IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (2019 DISCOVER), Manipal Institute of Technology, Manipal, Aug. 2019

  18. A. Kokate, P.M.Jadhav, “Sentiment Analysis using Convolution Neural Network ”, International Journal for Research in Engineering Application & Management, Vol. 5, no. 3, June 2019

  19. S. Begumpure, P.M.Jadhav, “Comprehensive Review Of Generic Object Detection Frameworks Using Deep Learning Approach,” IEEE International Conference on Contemporary Engineering and Technology, April, 26th-27th , 2019, Chennai.

  20. A.N.Pitale, A .A.Bendre, , R.V.Agashe, P.M.Jadhav, “Signal Conditioning Algorithms On Accelerometers In An Inertial Navigation System (INS),”  International Conference on Signal and Information Processing, Oct, 10, 2016,Vishnupur

  21. T.M.Pandit, P.M.Jadhav,A.C.Phadke, “Suspicious Object Detection In Surveillance Videos For Security Applications,” International Conference on Inventive Computation Technologies, Aug. 26, 2016, Coimbatore

  22. P.M.Jadhav, Dr.S.Kshirsagar, “Efficient Rate Control Scheme using Modified Inter- Layer Dependency for Spatial Scalability,”  Springer-Sadhana – Academy Proceedings in Engineering Sciences, Vol.41, no. 12, doi: 10.1007/s12046-016-0568-6, Nov. 2016.

  23. Prasad Yedurkar,P.M.Jadhav, “Study and Analysis of JSVM onTMS3208168”, International Journal of Innovations and Advancement in Computer ScienceVol. 3, No. 4, Jun. 2014.

  24. P.M.Jadhav, Dr.ShirishKshirsagar, “Independent Rate Control Scheme for Spatial Layer in H.264”,at IEEE International Conference on ,Advances in Recent Technologies in Communication and Computing-ARTCOM-2013, Sept. 19-20 2013, Bangalore

  25. Patharwalkar Shilpa S, Jadhav P M, “Complexity Control Using Inter Mode Decision In H.264/AVC Baseline Profile”, International Journal of Electronics and Communication Engineering. ISSN 0974-2166 Volume 6, No 1, 2013, pp. 57-65

  26. Mrs. MrunaliniChavaan,P.M.Jadhav, “Modified Macroblock Mode Decision Method for H.264/AVC”, International Journal of Engineering Research Technology, ISSN-2278-0181, Vol.1(02), No. 2012

  27. S.S.Tavse,P.M.Jadhav, M.R.Ingle, “Optimized Median Filter Implementation on FPGA Including Soft Processor”, International Journal of Emerging Technology and Advanced Engineering, ISSN-250-2459, Vol.2, No. 8, Aug. 2012

  28. Ranjana Kedar,P.M.Jadhav, M.R.Ingle,, “Implementation ofFast Computing Algorithm using Macroblock Motion Decision in H.264”, International Journal of Advances in Management, Technology and Engineering Sciences, ISSN-2249-7455, Vol.1, No.2, Mar. 2012

  29. Ranjana Kedar, P.M.Jadhav, M.R.Ingle, “Implementation of Fast Computing Algorithm using Macroblock Motion Decision in H.264”, 1stInternational Conference on Current Trends in Engineering and Technology, Mar. 2012.

  30. S.D.Oza,P.M.Jadhav, K.P.Joshi, “A Fast Block Matching Motion Estimation Algorithm in Video Coding Standards”, International Journal of Electronics, Communication & Soft Computing Science and Engineering(IJECSCSE) , Vol. 1, No. 1

  31. S.S.Paiharwalkar,P.M.Jadhav, “Fast Inter Mode Decision Algorithm for H.264 /AVC Baseline Profile for Mobile Video Conferencing”, International Journal of Engineering Sciences Research(IJESR)ISSN-2230-8504,e-ISSN-2230 8512, Oct. 2012

  32. K.A.Prabhudessai,P.M.Jadhav, “Frame Level Rate Control Algorithm for Temporal Scalability in Scalable Video Coding”, Emerging Trends in Electronics and Telecommunication, MIT COE, Pune, Dec. 2011.

  33. P.Dalal,  P.M.Jadhav, “Rate Control Algorithm for Spatial Video Coding”, Emerging Trends in Electronics and Telecommunication, MITCOE, Pune, Dec. 2011

  34. A.Patil,  P.M.Jadhav, “SCADA System for Plant Automation” ,National Conference on Emerging Technologies in Computer Science , Bangalore, Aug. 2010

  35. A.A.Bairagi, S.P.Newaskar, R.D.Shah, P.M.Jadhav, S.Kulkarni, “Development of Fast Motion Estimation Algorithm With High Accuracy” ,International Conference on Information Science, Communications and Applications ,Cancun, May 2005

Research Team
  1. An Automated Grape Cluster Weight Prediction System Using Deep Learning, Status; Granted- 20 2022 703 741

  2. A Multi-regression Grape Weight Prediction System and Methods , Status; Granted-2022/-6787

  3. Low Power and Low Area Mash 2-2 Modulator for Portable Music Players, Status: Granted-FA/536/MUM/2022


Guide for Major Projects


  • Deep Learning Techniques for Automated Image Captioning

  • Object detection and classification using sensor fusion of camera and LiDAR

  •  Image reconstruction using maximum entropy

  • Suspicious object detection in surveillance system

  • Sentiment analysis using CNN

  • Optimization of video coding standard for real time application

  • Rate control algorithm for H.264 AVC on embedded platform

  • Media player on Android Operating System

  • Motion Estimation Compensation algorithm using Video Object Plane concept in H.264 AVC

  • Speech Processing tool box

  • American sign language generator

  • DSP based pulse-Oxymeter

  • Speaker identification on TMS320C5402

Guide for 50+ Seminars


Some noteworthy seminars are:

  • Object detection using YOLO

  • Fusion of sensors to improve accuracy in autonomous vehicles

  • Algorithm

  • Advanced Video Coding Standard (H.264/AVC)

  • Optimized Implementation of Median Filter on FPGA

  • Developing a General Purpose Bitmap to Vector Conversion Algorithm for Embedded System Applications

  • Programming Adaptive Filters using Code Composer Studio of DSP Processor or Acoustic Echo Cancellation

  • Interfacing of I/O Devices to Digital Signal Processor for Acoustic Echo Cancellation

  • Music Analyzer

  • Speaker identification on TMS320C5402

Faculty Development Programme / Workshops Conducted

22 March 2019

Advanced Processors- TMS3206437

At Bharati Vidyapeeth Womens Engineering College 


24 Jan 2022 to 29Jan 2022

Resource person for the AICTE sponsored one-week STTP on "Machine Learning"

1 Week workshop


22 March 2019

Advanced Processors- TMS3206437

At Bharati Vidyapeeth Womens Engineering College 


22 March 2018

DSP Processors

for  the subject Advanced Processors,TE ( E & TC)

Video Analytics

26th May-30th May

Faculty Development Program on Signal, Image & Video Processing: A Practical Approach (SIVPAPA-2020)

SIVPAPA-2020 Day 5

SIVPAPA-2020 Day 5

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