Pravin Marotrao Ghate

@jspmrscoe.edu.in

Asst.Professor, Electronics & Telecommunication
JSPM's Rajarshi Shahu College of Engineering Pune

Pravin Marotrao Ghate


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https://researchid.co/pravinghate
15 Year of Experience in teaching .
6 International Paper 5 National Paper published
Two Patent

RESEARCH INTERESTS

Product Development ,Software development Speech Processing

FUTURE PROJECTS

Product development

Product for agriculture


Applications Invited
Students

Software development

Better management


Applications Invited
Students
15

Scopus Publications

43

Scholar Citations

3

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • RETINOPATHY DISEASE DETECTION AND CLASSIFICATION USING COORDINATE ATTENTION MODULE BASED CONVOLUTIONAL NEURAL NETWORK WITH LEAKY RECTIFIED LINEAR UNIT
    Pravin Balaso Chopade, Prabhakar N. Kota, Bhagvat D. Jadhav, Pravin Marotrao Ghate, Shriram Sadashiv Kulkarni
    Iium Engineering Journal, 2025
    The detection of Diabetic Retinopathy (DR) is an emergent research topic in recent decades, where DR is a primary cause of vision loss in humans. The existing techniques have limitations such as neuron death issues, vanishing gradient, and output offset. To overcome these issues, this paper proposes a Deep Learning (DL)-based technique for early and accurate DR detection. The Coordinate Attention Module (CAM) based Convolutional Neural Network (CNN) with Leaky Rectified Linear Unit (LReLU) is proposed for early and accurate detection of DR. The MESSIDOR dataset is preprocessed through the median filter to eliminate noise, and Contrast-Limited Adaptive Histogram Equalization (CLAHE) is utilized to increase the contrast level in an input image. The preprocessed images are given to Mayfly Optimization Algorithm-based Region Growing (MOARG) for image segmentation. Then, the features are extracted using ResNet50 and SqueezeNet, which extract deep learning features. The extracted features are given to CAM-based CNN with LReLU to detect DR, which overcomes the dead issues of neurons and minimizes the probability of inactive neurons. The proposed model achieves better results on the MESSIDOR datasets on the metrics of accuracy, precision, recall, specificity, f1-score, and Area Under Curve (AUC) values of about 99.72%, 99.46%, 99.25%, 99.61%, 99.37% and 99.14%, correspondingly, proving to be superior to the existing method, Capsule Network and Hybrid Adaptive DL based DR (HADL-DR). ABSTRAK: Pengesanan Retinopati Diabetik (DR) merupakan topik penyelidikan yang semakin mendapat perhatian dalam dekad-dekad kebelakangan ini, di mana DR merupakan punca utama kehilangan penglihatan pada manusia. Teknik sedia ada mempunyai beberapa kekangan seperti isu kematian neuron, vanishing gradient, dan output offset. Untuk mengatasi isu-isu ini, kertas ini mencadangkan teknik berasaskan Pembelajaran Mendalam (DL) untuk pengesanan awal dan tepat bagi DR. Modul Coordinate Attention Module (CAM) berasaskan Convolutional Neural Network (CNN) dengan Leaky Rectified Linear Unit (LReLU) dicadangkan untuk pengesanan awal dan tepat bagi DR. Dataset MESSIDOR diproses melalui penapis median yang digunakan untuk menghapuskan hingar, dan Contrast-Limited Adaptive Histogram Equalization (CLAHE) digunakan untuk meningkatkan tahap kontras pada imej input. Imej yang telah diproses diberikan kepada Algoritma Pengoptimuman Mayfly berasaskan Region Growing (MOARG) untuk segmentasi imej. Kemudian, ciri-ciri diekstrak menggunakan ResNet50 dan SqueezeNet yang mengekstrak ciri-ciri pembelajaran mendalam. Ciri-ciri yang diekstrak ini diberikan kepada CNN berasaskan CAM dengan LReLU untuk pengesanan DR, yang mengatasi isu kematian neuron dan meminimumkan kebarangkalian neuron tidak aktif. Model yang dicadangkan mencapai keputusan yang lebih baik pada dataset MESSIDOR berdasarkan metrik ketepatan, ketepatan, panggilan semula, kekhususan, skor f1, dan nilai Kawasan di Bawah Lengkung (AUC) iaitu sekitar 99.72%, 99.46%, 99.25%, 99.61%, 99.37% dan 99.14%, masing-masing, membuktikan keunggulannya berbanding kaedah sedia ada, Capsule Network dan Hybrid Adaptive DL berasaskan DR (HADL-DR).
  • GLOBAL-LOCAL SELF-ATTENTION BASED LONG SHORT-TERM MEMORY WITH OPTIMIZATION ALGORITHM FOR SPEAKER IDENTIFICATION
    Pravin Marotrao Ghate, Bhagvat D. Jadhav, Shriram Sadashiv Kulkarni, Pravin Balaso Chopade, Prabhakar N. Kota
    Iium Engineering Journal, 2025
    Speaker identification (SI) involves recognizing a speaker from a group of unknown speakers, while speaker verification (SV) determines if a given voice sample belongs to a particular person. The main drawbacks of SI are session variability, noise in the background, and insufficient information. To mitigate the limitations mentioned above, this research proposes Global Local Self-Attention (GLSA) based Long Short-Term Memory (LSTM) with Exponential Neighborhood – Grey Wolf Optimization (EN-GWO) method for effective speaker identification using TIMIT and VoxCeleb 1 datasets. The GLSA is incorporated in LSTM, which focuses on the required data, and the hyperparameters are tuned using the EN-GWO, which enhances speaker identification performance. The GLSA-LSTM with EN-GWO method acquires an accuracy of 99.36% on the TIMIT dataset, and an accuracy of 93.45% on the VoxCeleb 1 datasets, while compared to SincNet and Generative Adversarial Network (SincGAN) and Hybrid Neural Network – Support Vector Machine (NN-SVM). ABSTRAK: Pengenalpastian pembicara (Speaker Identification, SI) melibatkan pengenalan pembicara daripada kumpulan pembicara yang tidak dikenali, manakala pengesahan pembicara (Speaker Verification, SV) menentukan sama ada sampel suara tertentu milik seseorang individu. Kekurangan utama dalam SI ialah variasi sesi, bunyi latar belakang, dan maklumat yang tidak mencukupi. Untuk mengatasi kekangan tersebut, kajian ini mencadangkan kaedah Global Local Self-Attention (GLSA) berasaskan Long Short-Term Memory (LSTM) dengan Pengoptimuman Grey Wolf Jiranan Eksponen (EN-GWO) bagi pengenalpastian pembicara yang berkesan menggunakan set data TIMIT dan VoxCeleb 1. GLSA digabungkan dalam LSTM yang memberi tumpuan pada data yang diperlukan, manakala parameter hiper ditala menggunakan EN-GWO untuk meningkatkan prestasi pengenalpastian pembicara. Kaedah GLSA-LSTM dengan EN-GWO mencapai ketepatan 99.36% pada dataset TIMIT dan ketepatan 93.45% pada dataset VoxCeleb 1, berbanding dengan SincNet dan Generative Adversarial Network (SincGAN) serta Hybrid Neural Network – Support Vector Machine (NN-SVM).
  • SIMULATED ANNEALING-SALP SWARM ALGORITHM BASED VARIATIONAL AUTOENCODER FOR PEAK-TO-AVERAGE POWER RATIO REDUCTION
    Prabhakar Narasappa Kota, Pravin Balaso Chopade, Bhagvat D Jadhav, Shriram Sadashiv Kulkarni, Pravin Marotrao Ghate
    International Journal of Computer Networks and Communications, 2025
    Orthogonal Frequency Division Multiplexing (OFDM) have achieved significant advancements in spectral effectiveness and data rates within wireless communication systems. However, it is accompanied by a critical challenge: the high Peak-to-Average Power Ratio (PAPR). This issue demands attention and effective solutions to ensure optimum performance and reliability of OFDM-based systems. Currently, deep Learning (DL) algorithms perform well on end-to-end wireless communication systems. This study introduces a novel approach to PAPR reduction in OFDM systems by integrating a Simulated AnnealingSalp Swarm Algorithm (SA-SSA) with a Variational AutoEncoder (VAE). The proposed method effectively mitigates peaks while preserving favorable spectral properties, thereby facilitating seamless PAPR migration. The SA-SSA - based VAE method is used to develop a peak-canceling signal method depending on the input signal which reduces the PAPR signal. Constellation mapping and remapping of symbols are considered in each subcarrier of the VAE method that minimizes the Bit Error Rate (BER) and PAPR in OFDM systems. To further improve the performance of VAE, proposed an SA-SSA algorithm that tuned the hyperparameters of the VAE method to select optimum hyperparameters of VAE for better performance. The performance of the developed method is analyzed with characteristics of BER, Symbol Error Rate (SER), and Complementary Cumulative Distribution Function (CCDF) under various subcarriers. The proposed method obtained less PAPR of 1.9 dB, 2.0 dB, 2.4 dB, 2.8 dB, and 3.2 dB for 64, 128, 256, 512, and 1024 subcarriers which is less when compared to existing methods like Hyperparameter Tuned Deep Learning based Stacked Sparse Autoencoder (HPT-SSAE and Conditionally Applied Neural Network (CANN).
  • An optimized network for drought prediction using satellite images
    Bhagvat D Jadhav, Pravin Marotrao Ghate, Prabhakar Narasappa Kota, Shankar Dattatray Chavan, Pravin Balaso Chopade
    Remote Sensing Applications Society and Environment, 2024
  • An efficient disaster management system based on deep learning in bio-inspired wireless sensor network
    Engineering and Applied Science Research, 2024
  • Energy Efficient Multiobjective Improved Wild Horse Optimization for Clustering and Routing in Wireless Sensor Networks
    International Journal of Intelligent Engineering and Systems, 2024
  • An Improved Model for Plant Disease Analysis Using Attention Based Capsule Network
    International Journal of Intelligent Engineering and Systems, 2024
  • Optimized intelligent speech signal verification system for identifying authorized users
    Engineering and Applied Science Research, 2023
  • IOT RESOURCE ALLOCATION AND OPTIMIZATION USING IMPROVED REPTILE SEARCH ALGORITHM
    Prabhakar Narasappa Kota, Pravin Balaso Chopade, Bhagvat D. Jadhav, Pravin Marotrao Ghate, Shankar Dattatray Chavan
    International Journal of Computer Networks and Communications, 2023
    The Internet of Things (IoT) is a dispersed network system that connects the world through the Internet. The architecture of IoT consists of more gateways and resources which cannot be allocated in a manual process. The allocation of resources in IoT is a challenging process due to the higher consumption of energy and high latency rate. To overcome the challenges in existing works, this research introduced an Improved Reptile Search Algorithm (IRSA) to solve the optimization problem which occurs during the time of allocation resources among IoT networks. IRSA employs the methodology of levy flight and cross-over to update the candidate position and enhance the search speed in a single iteration. The proposed method consumes less energy and has low latency during data transmission from User equipment (UE) to the base station.IRSA has been compared with the existing Scalable Resource Allocation Framework (SRAF) and Improved Chaotic Firefly Algorithm (ICFA). The obtained experimental results show that the proposed IRSA attained better performance with an allocation rate of 96.40% which is comparatively higher than SRAF and ICFA with 92.40% and 91.67% respectively.
  • Lucy Richardson and Mean Modified Wiener Filter for Construction of Super-Resolution Image
    Pravin Balaso Chopade, Prabhakar N. Kota, Bhagvat D. Jadhav, Pravin Marotrao Ghate, Shankar Dattatray Chavan
    International Journal of Electrical and Computer Engineering Systems, 2023
    The ultimate goal of the Super-Resolution (SR) technique is to generate the High-Resolution (HR) image by combining the corresponding images with Low-Resolution (LR), which is utilized for different applications such as surveillance, remote sensing, medical diagnosis, etc. The original HR image may be corrupted due to various causes such as warping, blurring, and noise addition. SR image reconstruction methods are frequently plagued by obtrusive restorative artifacts such as noise, stair casing effect, and blurring. Thus, striking a balance between smoothness and edge retention is never easy. By enhancing the visual information and autonomous machine perception, this work presented research to improve the effectiveness of SR image reconstruction The reference image is obtained from DIV2K and BSD 100 dataset, these reference LR image is converted as composed LR image using the proposed Lucy Richardson and Modified Mean Wiener (LR-MMWF) Filters. The possessed LR image is provided as input for the stage of bicubic interpolation. Afterward, the initial HR image is obtained as output from the interpolation stage which is given as input for the SR model consisting of fidelity term to decrease residual between the projected HR image and detected LR image. At last, a model based on Bilateral Total Variation (BTV) prior is utilized to improve the stability of the HR image by refining the quality of the image. The results obtained from the performance analysis show that the proposed LR-MMW filter attained better PSNR and Structural Similarity (SSIM) than the existing filters. The results obtained from the experiments show that the proposed LR-MMW filter achieved better performance and provides a higher PSNR value of 31.65dB whereas the Filter-Net and 1D,2D CNN filter achieved PSNR values of 28.95dB and 31.63dB respectively.
  • Design of a low-cost welding machine controller with a novel control algorithm for an enhanced HF TIG welding process
    Dnyaneshwar Vitthal Sahane, Pravin M Ghate, Ajay N Paithane
    Engineering Research Express, 2022
  • Syllable-Based Concatenative Speech Synthesis for Marathi Language
    Pravin M. Ghate, Suresh D. Shirbahadurkar
    Lecture Notes in Networks and Systems, 2019
  • Naturalness improvement in text to speech synthesis using threshold amplitude of the syllable (Marathi language)
    Pravin M Ghate, S. D. Shirbhadurkar
    IEEE International Conference on Power Control Signals and Instrumentation Engineering Icpcsi 2017, 2018
  • A simple analytical model of 4H-SiC MOSFET for high temperature circuit simulations
    Ganesh C. Patil, Santosh C. Wagaj, Pravin M. Ghate
    11th IEEE India Conference Emerging Trends and Innovation in Technology Indicon 2014, 2015
  • Automatic speaker recognition system
    P. M. Ghate, Shraddha Chadha, Aparna Sundar, Ankita Kambale
    Advances in Intelligent Systems and Computing, 2013

RECENT SCHOLAR PUBLICATIONS

  • Machine Learning and IoT Applications in Optimizing MIDREX Shaft Furnace Operations
    SCW Pravin Ghate , Mohan Shigade , Shailesh Hambrde , S,M,Deokar
    Journal of Information Systems Engineering and Management 10 (41), 577-585 , 2025
    2025
  • Evaluation of YOLOv8 and SSD Object Detection Models for Pothole Detection Systems
    SK Samarth Sarange1, Prathamesh Manmat2, Pravin Ghate3
    Journal of Information Systems Engineering and Management, 7 , 2025
    2025
  • Global-Local Self-Attention-Based Long Short-Term Memory with Optimization Algorithm for Speaker Identification
    PM Ghate, BD Jadhav, SS Kulkarni, PB Chopade, PN Kota
    IIUM Engineering Journal 26 (1), 278-292 , 2025
    2025
    Citations: 1
  • Retinopathy Disease Detection and Classification Using a Coordinate Attention Module-Based Convolutional Neural Network with Leaky Rectified Linear Unit
    PB Chopade, PN Kota, BD Jadhav, PM Ghate, SS Kulkarni
    IIUM Engineering Journal 26 (1), 129-147 , 2025
    2025
    Citations: 2
  • Energy Efficient Multiobjective Improved Wild Horse Optimization for Clustering and Routing in Wireless Sensor Networks.
    SS Kulkarni, PM Ghate, BD Jadhav, PB Chopade, PN Kota
    International Journal of Intelligent Engineering & Systems 17 (6) , 2024
    2024
    Citations: 2
  • An optimized network for drought prediction using satellite images
    BD Jadhav, PM Ghate, PN Kota, SD Chavan, PB Chopade
    Remote Sensing Applications: Society and Environment 36, 101278 , 2024
    2024
    Citations: 1
  • An Improved Model for Plant Disease Analysis Using Attention Based Capsule Network.
    BD Jadhav, PM Ghate, PB Chopade, PN Kota, SS Kulkarni
    International Journal of Intelligent Engineering & Systems 17 (5) , 2024
    2024
    Citations: 2
  • An efficient disaster management system based on deep learning in bio-inspired wireless sensor network
    SD Chavan, PB Chopade, BD Jadhav, PN Kota, PM Ghate
    Engineering and Applied Science Research 51 (2), 152-163 , 2024
    2024
  • Significance of Blockchain Technology in Mean Kinetic Temperature Monitoring for Cold Chain Management
    SW Swati D.Kale, Shailaja C.Patil , charushila V.Rane , Pravin Ghate
    GRADIVA REVIEW JOURNAL 10 (2), 159-164 , 2024
    2024
  • Novel Approach of ECG Signal Classification Using CNN model
    SCW B D Jadhav, P.M.Ghate
    The International journal of analytical and experimental modal analysis 16 … , 2024
    2024
  • Optimized intelligent speech signal verification system for identifying authorized users
    PM Ghate, BD Jadhav, PN Kota, SD Chavan, PB Chopade
    Engineering and Applied Science Research 50 (6), 525-537 , 2023
    2023
  • Lucy Richardson and Mean Modified Wiener Filter for Construction of Super-Resolution Image
    PB Chopade, PN Kota, BD Jadhav, P Marotrao Ghate, ...
    International journal of electrical and computer engineering systems 14 (5 … , 2023
    2023
    Citations: 2
  • IOT resource allocation and optimization using improved reptile search algorithm
    PN Kota, PB Chopade, BD Jadhav, PM Ghate, SD Chavan
    Int J Comput Netw Commun 15 (4), 39-53 , 2023
    2023
    Citations: 4
  • Design of a low-cost welding machine controller with a novel control algorithm for an enhanced HF TIG welding process
    DV Sahane, PM Ghate, AN Paithane
    Engineering Research Express 4 (2), 025025 , 2022
    2022
    Citations: 3
  • Model for Conversion of Biodegradable Waste into Organic Fertiliser
    PM Ghate
    TEST ENGINEERING AND MANAGEMENT 83 (Publication Issue), 26480 - 26486 , 2020
    2020
  • QRS detection Using Empirical Mode Decomposition Method for Human Computer Interface
    PMG A. N. Paithane, Sakshi A Paithane
    International Journal of Advanced Science and Technology 29 (7), 702 - 712. , 2020
    2020
    Citations: 3
  • Land use Land Cover Mapping using Modified Ant Colony Optimization Technique
    PMG Bhagavat. D. Jadhav,Chandrama. G. Thoart ,Ajay. N. Paithane
    International Journal of Innovative Technology and Exploring Engineering … , 2020
    2020
  • Syllable-Based Concatenative Speech Synthesis for Marathi Language
    PM Ghate, SD Shirbahadurkar
    Information and Communication Technology for Competitive Strategies … , 2018
    2018
    Citations: 2
  • Concatenation of syllable by anchor frame to improve Naturalness in speech synthesis for Marathi language (India)
    PM Ghate
    International Journal of Pure and Applied Mathematics 118 (Special issues), 1-15 , 2018
    2018
  • Text to Speech System for Marathi Language using Syllable Unit (India) to Improve the Naturalness
    PM Ghate, SD Shirbhadurkar
    Journal of Information and Language Engineering 1 (1) , 2018
    2018

MOST CITED SCHOLAR PUBLICATIONS

  • A simple analytical model of 4H-SiC MOSFET for high temperature circuit simulations
    GC Patil, SC Wagaj, PM Ghate
    2014 Annual IEEE India Conference (INDICON), 1-5 , 2014
    2014
    Citations: 12
  • IOT resource allocation and optimization using improved reptile search algorithm
    PN Kota, PB Chopade, BD Jadhav, PM Ghate, SD Chavan
    Int J Comput Netw Commun 15 (4), 39-53 , 2023
    2023
    Citations: 4
  • Automatic speaker recognition system
    PM Ghate, S Chadha, A Sundar, A Kambale
    Proceedings of International Conference on Advances in Computing, 1037-1044 , 2013
    2013
    Citations: 4
  • Design of a low-cost welding machine controller with a novel control algorithm for an enhanced HF TIG welding process
    DV Sahane, PM Ghate, AN Paithane
    Engineering Research Express 4 (2), 025025 , 2022
    2022
    Citations: 3
  • QRS detection Using Empirical Mode Decomposition Method for Human Computer Interface
    PMG A. N. Paithane, Sakshi A Paithane
    International Journal of Advanced Science and Technology 29 (7), 702 - 712. , 2020
    2020
    Citations: 3
  • Retinopathy Disease Detection and Classification Using a Coordinate Attention Module-Based Convolutional Neural Network with Leaky Rectified Linear Unit
    PB Chopade, PN Kota, BD Jadhav, PM Ghate, SS Kulkarni
    IIUM Engineering Journal 26 (1), 129-147 , 2025
    2025
    Citations: 2
  • Energy Efficient Multiobjective Improved Wild Horse Optimization for Clustering and Routing in Wireless Sensor Networks.
    SS Kulkarni, PM Ghate, BD Jadhav, PB Chopade, PN Kota
    International Journal of Intelligent Engineering & Systems 17 (6) , 2024
    2024
    Citations: 2
  • An Improved Model for Plant Disease Analysis Using Attention Based Capsule Network.
    BD Jadhav, PM Ghate, PB Chopade, PN Kota, SS Kulkarni
    International Journal of Intelligent Engineering & Systems 17 (5) , 2024
    2024
    Citations: 2
  • Lucy Richardson and Mean Modified Wiener Filter for Construction of Super-Resolution Image
    PB Chopade, PN Kota, BD Jadhav, P Marotrao Ghate, ...
    International journal of electrical and computer engineering systems 14 (5 … , 2023
    2023
    Citations: 2
  • Syllable-Based Concatenative Speech Synthesis for Marathi Language
    PM Ghate, SD Shirbahadurkar
    Information and Communication Technology for Competitive Strategies … , 2018
    2018
    Citations: 2
  • COAP BASED HEALTHCARE MONITORING SYSTEM
    SUD P.M.GHATE
    Proceedings of SARC International Conference , 2017
    2017
    Citations: 2
  • A survey on methods of tts and various test for evaluating the quality of synthesized speech
    P Ghate, SD Shirbahadurkar
    Int J Dev Res 7, 15236-15239 , 2017
    2017
    Citations: 2
  • Global-Local Self-Attention-Based Long Short-Term Memory with Optimization Algorithm for Speaker Identification
    PM Ghate, BD Jadhav, SS Kulkarni, PB Chopade, PN Kota
    IIUM Engineering Journal 26 (1), 278-292 , 2025
    2025
    Citations: 1
  • An optimized network for drought prediction using satellite images
    BD Jadhav, PM Ghate, PN Kota, SD Chavan, PB Chopade
    Remote Sensing Applications: Society and Environment 36, 101278 , 2024
    2024
    Citations: 1
  • Naturalness improvement in text to speech synthesis using threshold amplitude of the syllable (Marathi language)
    PM Ghate, SD Shirbhadurkar
    2017 IEEE International Conference on Power, Control, Signals and … , 2017
    2017
    Citations: 1
  • Machine Learning and IoT Applications in Optimizing MIDREX Shaft Furnace Operations
    SCW Pravin Ghate , Mohan Shigade , Shailesh Hambrde , S,M,Deokar
    Journal of Information Systems Engineering and Management 10 (41), 577-585 , 2025
    2025
  • Evaluation of YOLOv8 and SSD Object Detection Models for Pothole Detection Systems
    SK Samarth Sarange1, Prathamesh Manmat2, Pravin Ghate3
    Journal of Information Systems Engineering and Management, 7 , 2025
    2025
  • An efficient disaster management system based on deep learning in bio-inspired wireless sensor network
    SD Chavan, PB Chopade, BD Jadhav, PN Kota, PM Ghate
    Engineering and Applied Science Research 51 (2), 152-163 , 2024
    2024
  • Significance of Blockchain Technology in Mean Kinetic Temperature Monitoring for Cold Chain Management
    SW Swati D.Kale, Shailaja C.Patil , charushila V.Rane , Pravin Ghate
    GRADIVA REVIEW JOURNAL 10 (2), 159-164 , 2024
    2024
  • Novel Approach of ECG Signal Classification Using CNN model
    SCW B D Jadhav, P.M.Ghate
    The International journal of analytical and experimental modal analysis 16 … , 2024
    2024

RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)

Patent

Industry, Institute, or Organisation Collaboration

SSGR Pvt Ltd

INDUSTRY EXPERIENCE

Two year