Priyadarshi Kanungo

Scopus Publications

Camouflaged object detection using hybrid-deep learning model
Isha Padhy, Teja Sai Chenna Malleswar Rao J, Venkata Koti Reddy CH, Priyadarshi Kanungo, Sampa Sahoo
Multimedia Tools and Applications, 2025
Non-Uniform Illumination Image Thresholding Using MLP
Tapaswini Pattnaik, Priyadarshi Kanungo
2025 4th International Conference on Range Technology Icort 2025, 2025
One well-known and popular method for classifying objects and backgrounds in real time is thresholding. Because of its simplicity, it is especially well-suited for real-time applications. However, because background and object pixels have overlapping gray-level distributions, thresholding loses effectiveness when used on images taken in uneven lighting. In images with non-uniform lighting, global thresholding techniques fail to binarize because of an absence of visible bimodal histograms. The choice of the initial window size or sub-image size, which differs for each image, affects how well window-based or image partition-based local thresholding performs. Furthermore, the bimodal testing criterion function is necessary for the partitioning process to be effective. Choosing the right criterion function for bimodality and beginning window size for image partitioning are important issues in adaptive thresholding techniques. The suggested approach takes into account machine learning (ML) techniques to increase the accuracy of uneven light image thresholding. The objective is to use global thresholding to binarize an image and predict the non-uniform illumination surface. The suggested MLP-based approach outperforms the local and surface-based thresholding methods in terms of average performance metric.
Non-Uniform Illumination Image Thresholding based on k-means clustering and MLR
Tapaswini Pattnaik, Priyadarshi Kanungo
2nd International Conference on Cognitive Green and Ubiquitous Computing IC Cgu 2025, 2025
Role of 5G Network in Smart Cities Toward Green Technology
5g Green Communication Networks for Smart Cities, 2025
Brain tumor Segmentation using DeepAttRes-Unet based transfer learning
Pallavi Priyadarshini, Smita Parija, Priyadarshi Kanungo, Prabodh Kumar Sahoo, Tejaswini Kar
Iet Conference Proceedings, 2025
Early-stage brain tumor identification is a difficult issue that is well handled by machine learning (ML) and deep learning (DL) classifiers. In order to identify the best classifier, a comparison analysis of the various ML classifier types is conducted in this work.Transfer learning allows us to reuse previously taught models. Transfer learning refers to applying previously acquired information to new activities.The identification and detection of brain tumors with MRIs is tough to perform manually. When done manually, detecting and classifying brain tumors with MRIs is a difficult process. Automation of these processes has become necessary. However, developing deep learning models from scratch on large datasets may be computationally intensive. This research offers a transfer learning for image segmentation and prediction of tumors. We utilized models and formed an Unet to segment the tissues in this work. We utilized the LGG dataset, which has 110 patient records, to conduct segmentation. We developed a unique residual model as the foundation for creating the unet from scratch and doing multispectral image segmentation. The suggested model works well, and its performance is measured by the Dice coefficient, Jaccard index, and IoU. The model produces an accuracy mean of 0.99 and a Dice coefficient mean of 0.8428.
Advanced Diagnostic Framework with Vision Transformer for Multiclass Skin Disease Classification
Barunaditya Mohanty, Ayush Singhal, Brajesh Kumar, Praveen Kumar Yadav, Priyadarshi Kanungo, Ram Chandra Barik
Lecture Notes in Networks and Systems, 2025
Retraction Note: An improved and low-complexity neural network model for curved lane detection of autonomous driving system (Soft Computing, (2023), 27, 1, (493-504), 10.1007/s00500-021-05815-0)
Safwan Ghanem, Priyadarshi Kanungo, Ganapati Panda, Pritee Parwekar
Soft Computing, 2024
Multigrade brain tumor classification in MRI images using Fine tuned efficientnet
Pallavi Priyadarshini, Priyadarshi Kanungo, Tejaswini Kar
E Prime Advances in Electrical Engineering Electronics and Energy, 2024
Medical imaging plays a vital role in detecting and treating brain tumors. Malignant or nonmalignant brain tissue’s abnormal growth causes long-term brain damage. It is crucial to detect and properly categorize the kind of brain tumor. Specialists normally use MRI to create high-contrast grayscale brain images to segment them. Convolutional neural networks (CNN) driven by deep learning (DL) have transformed computer-assisted testing systems by producing good results in a wide range of medical imaging analytics applications, including tumor diagnosis in the brain. The paper introduces a lightweight fine-tuned Convolutional Neural Network EfficientNet ’ECNN’ to detect brain tumors. In this study, we provide a transfer learning-based measurement strategy for grouping cerebrum growths in three distinct datasets with different classifications, such as meningioma, glioma, and pituitary growth, using fine-tuned EfficientNets. The findings of this research rely on Efficient Nets to classify brain tumors in three different types of datasets utilizing a fine-tuned transfer learning mechanism. With EfficientNetV2S as the system’s foundation, our proposed way of fine-tunned pre-trained EfficientNetV2S model outperformed for all datasets over state of the art methods. The effectiveness of the suggested model has been assessed using performance metrics, and outcomes were compared to those produced using state-of-the-art approaches. The average test accuracy, recall, precision, and sensitivity score are 98.48%, 98%, 98.5%, and 98.71%, respectively.
Video shot-boundary detection: issues, challenges and solutions
T. Kar, P. Kanungo, Sachi Nandan Mohanty, Sven Groppe, Jinghua Groppe
Artificial Intelligence Review, 2024
The integration of high data transmission rates and the recent digital multimedia technology, paves the way to access a huge amount of video over the internet, in seconds. Additionally, uploading videos to different websites is no more confined to expert software professionals resulting in duplication of video data which led to exorbitant growth of multimedia information in cyberspace in a short span of time. This necessitates the development of efficient data management techniques including storage, searching and annotation mechanism. Automatic shot boundary detection is considered to be the first and foremost step towards such management. It is a booming area of research gaining attention in the domain of image processing, computer vision and pattern recognition. In this review paper, we present a detailed description of the methods and algorithms of shot boundary detection, reported in the last two decades. This review shows that using multiple features performs well in comparison to using only a single feature in the shot boundary detection problem although it leads to higher complexity. The major sources of disturbance in the boundary detection are the sudden illumination variation and presence of high motion in the video. An adaptive threshold outperforms a single global threshold in the boundary detection problem and the threshold requirement can be avoided through learning based strategies at the cost of larger training data and higher computation time. Moreover the present review includes a critical analysis of relative merits and demerits of existing algorithms and finally opens promising research directions in the area.
Multiple linear regression based illumination normalization for non-uniform light image thresholding
Tapaswini Pattnaik, Priyadarshi Kanungo, Tejaswini Kar, Prabodh Kumar Sahoo
E Prime Advances in Electrical Engineering Electronics and Energy, 2024
Thresholding-based two-class image binarization is one of the simplest and most popular approaches. However, the performance of global thresholding degrades under non-uniform lighting conditions. Local thresholding methods are widely used for binarizing uneven light images. The appropriate choice of the initial size of the window and designing the bimodal criteria function are the most challenging tasks for the local thresholding approaches. Therefore, to make it simpler, in this work, a novel approach is developed to improve the efficacy of binarizing any uneven light images. To begin with, a two stage approach is developed to extract valid training sample points from the uneven light images for estimating the illumination surface. In addition, the Multiple-Linear-Regression (MLR) method is applied on the extracted training sample points to estimate the illumination surface. Furthermore, the estimated illumination surface is used to normalize the non-uniform light of the image to binarize the image using Otsu’s global thresholding. The proposed approach is validated on different variants of uneven light images and with six different states of art uneven light image binarization approaches. It is observed from the simulations that the performance of the proposed approach outperforms the other approaches in qualitative as well as quantitative measures. Further, the binarization of uneven document image methods are not effective on object background binarization of uneven images. The proposed approach has the average F-Measure (F1) score of 0.98, average Jaccard Index (JI) score of 0.97, average Percentage of Misclassification Error (PME) score of 1.10 and the computational complexity of 2.64 sec.
Multiclass Classification of Camouflage Images Using Combined WLD and LPQ Feature Set Using a ANN Classifier
Isha Padhy, Priyadarshi Kanungo, Sampa Sahoo
Lecture Notes in Electrical Engineering, 2024
Predominant musical instrument detection using ensemble learning
S Pal, T. Kar, P. Kanungo
Esic 2024 4th International Conference on Emerging Systems and Intelligent Computing Proceedings, 2024
An Efficient Low Complex-Functional Link Artificial Neural Network-Based Framework for Uneven Light Image Thresholding
Tapaswini Pattnaik, Priyadarshi Kanungo, Prabodh Kumar Sahoo, Tejaswini Kar, Prince Jain, Mohamed S. Soliman, Mohammad Tariqul Islam
IEEE Access, 2024
Lane detection under artificial colored light in tunnels and on highways: an IoT-based framework for smart city infrastructure
Safwan Ghanem, Priyadarshi Kanungo, Ganapati Panda, Suresh Chandra Satapathy, Rohit Sharma
Complex and Intelligent Systems, 2023
A gradient based dual detection model for shot boundary detection
T. Kar, P. Kanungo
Multimedia Tools and Applications, 2023
Brain Tumor Detection and Classification from MRI Images Using Cascaded Deep Neural Networks
Pallavi Priyadarshini, Abdul Kayom Md. Khairuzzaman, Priyadarshi Kanungo
Lecture Notes in Electrical Engineering, 2023
Composer Identification in Classical Genre
S. Pal, T. Kar, P. Kanungo, Tapaswini Pattnaik
2023 IEEE 3rd International Conference on Applied Electromagnetics Signal Processing and Communication Aespc 2023, 2023
An improved and low-complexity neural network model for curved lane detection of autonomous driving system
Safwan Ghanem, Priyadarshi Kanungo, Ganapati Panda, Pritee Parwekar
Soft Computing, 2023
Entropy feature and peak-means clustering based slowly moving object detection in head and shoulder video sequences
Prabodh Kumar Sahoo, Priyadarshi Kanungo, Satyasis Mishra, Bibhu Prasad Mohanty
Journal of King Saud University Computer and Information Sciences, 2022
Illumination Insensitive Video Cut Detection Using Phase Congruency
T. Kar, P. Kanungo, Vinod Jha
Lecture Notes in Networks and Systems, 2022
A YCbCr Model Based Shadow Detection and Removal Approach On Camouflaged Images
Isha Padhy, Priyadarshi Kanungo, Sampa Sahoo
Proceedings 2022 Oits International Conference on Information Technology Ocit 2022, 2022
Automatic Cut Detection: A Probability Based Approach
Tejaswini Kar, P. Kanungo, Vinod Jha
Lecture Notes in Electrical Engineering, 2022
Customized YOLOv3 model for face detection in crowded images
Yasmin Al Othmani, Priyadarshi Kanungo, Safwan Ghanem, Abd Alaziz Alnaeb
2022 6th International Conference on Computing Communication Control and Automation Iccubea 2022, 2022
GMM Based Adaptive Thresholding for Uneven Lighting Image Binarization
Tapaswini Pattnaik, Priyadarshi Kanungo
Journal of Signal Processing Systems, 2021
Adaptive Window Selection for Non-uniform Lighting Image Thresholding
Tapaswini Pattnaik, Priyadarshi Kanungo
Electronic Letters on Computer Vision and Image Analysis, 2021
Face Recognition from Partial Face Data
Safa Alfattama, Priyadarshi Kanungo, Sukant Kishoro Bisoy
2021 International Conference in Advances in Power Signal and Information Technology Apsit 2021, 2021
Performance Evaluation of Learning Based Frameworks for Devanagari Character Recognition
Saptarshi Kattyayan, T. Kar, P. Kanungo
7th IEEE Uttar Pradesh Section International Conference on Electrical Electronics and Computer Engineering Upcon 2020, 2020
Abrupt Scene Change Detection Using Block Based Local Directional Pattern
T. Kar, P. Kanungo
Advances in Intelligent Systems and Computing, 2020
Motion and illumination defiant cut detection based on Weber features
Tejaswini Kar, Priyadarshi Kanungo
Iet Image Processing, 2018
A fast valley-based segmentation for detection of slowly moving objects
P. K. Sahoo, P. Kanungo, S. Mishra
Signal Image and Video Processing, 2018
Neighbourhood decision based impulse noise filter
Aswini Kumar Samantaray, Priyadarshi Kanungo, Bibhuprasad Mohanty
Iet Image Processing, 2018
Video shot boundary detection based on Hilbert and wavelet transform
T. Kar, P. Kanungo
Proceedings 2017 2nd International Conference on Man and Machine Interfacing Mami 2017, 2018
Welcome to MAMI 2017
Proceedings 2017 2nd International Conference on Man and Machine Interfacing Mami 2017, 2018
Valley based multiclass thresholding for color image segmentation
Tapaswini Pattnaik, P. Kanungo
Proceedings 2017 2nd International Conference on Man and Machine Interfacing Mami 2017, 2018
Neighborhood based codebook model for moving object segmentation
P. Kanungo, A. Narayan, P. K. Sahoo, S. Mishra
Proceedings 2017 2nd International Conference on Man and Machine Interfacing Mami 2017, 2018
A simple and fast automatic face colour identification for reducing the search space
Rajeswari, P. Kanungo, B. P. Mohanty, K. S. Mohanty
Proceedings 2017 2nd International Conference on Man and Machine Interfacing Mami 2017, 2018
A motion and illumination resilient framework for automatic shot boundary detection
T. Kar, P. Kanungo
Signal Image and Video Processing, 2017
Cut detection using local image descriptor
T. Kar, P. Kanungo
2016 IEEE Uttar Pradesh Section International Conference on Electrical Computer and Electronics Engineering Upcon 2016, 2017
Cut detection using block based center symmetric local binary pattern
P. Kanungo, T. Kar
Proceedings 2015 International Conference on Man and Machine Interfacing Mami 2015, 2016
Welcome to MAMI2015
Proceedings 2015 International Conference on Man and Machine Interfacing Mami 2015, 2016
A texture based method for scene change detection
T. Kar, P. Kanungo
2015 IEEE Power Communication and Information Technology Conference Pcitc 2015 Proceedings, 2016
Three frame based adaptive background subtraction
P.K. Sahoo, P. Kanungo, K. Parvathi
2014 International Conference on High Performance Computing and Applications Ichpca 2014, 2015
Automatic Lane Detection in NH5 of Odisha
P. Kanungo, S. K. Mishra, S. Mahapatra, U. R. Sahoo, U. S. Kr. Sah, V. Taunk
Advances in Intelligent Systems and Computing, 2015
Automatic cut detection based video segmentation
K.S. Mohanty, P. Kanungo
Proceedings 2013 International Symposium on Computational and Business Intelligence Iscbi 2013, 2013
First order neighborhood decision based median filter
Aswini Kumar Samantaray, Priyadarshi Kanungo
Proceedings of the 2012 World Congress on Information and Communication Technologies Wict 2012, 2012
Genetic algorithm based RNN structure for rayleigh fading MIMO channel estimation
G. Routraya, P. Kanungo
Procedia Engineering, 2012
Performance analysis of AODV, DSR, OLSR and DSDV routing protocols using NS2 simulator
S. Mohapatra, P. Kanungo
Procedia Engineering, 2012
A modified gray level co-occurrence matrix based thresholding for object background classification
A. Dash, P. Kanungo, B.P. Mohanty
Procedia Engineering, 2012
Comparative performance analysis of MANET routing protocols using NS2 simulator
S. Mohapatra, P. Kanungo
Communications in Computer and Information Science, 2011
Rayleigh fading MIMO channel prediction using RNN with genetic algorithm
G. Routray, P. Kanungo
Communications in Computer and Information Science, 2011
Development of de based adaptive techniques for nonlinear system identification
P. K. Khuntia, Benudhar Sahu, P. Kanungo
2011 International Conference on Recent Trends in Information Systems Retis 2011 Proceedings, 2011
Parallel genetic algorithm based adaptive thresholding for image segmentation under uneven lighting conditions
P. Kanungo, P. K. Nanda, A. Ghosh
Conference Proceedings IEEE International Conference on Systems Man and Cybernetics, 2010
Parallel genetic algorithm based clustering for object and background classification
P. Kanungo, P. K. Nanda, A. Ghosh
Machine Interpretation of Patterns Image Analysis and Data Mining, 2010
Detection of earth surface cracks using parallel genetic algorithm based thresholding
Priyadarshi Kanungo, Pradipta Kumar Nanda, Ashish Ghosh
Act 2009 International Conference on Advances in Computing Control and Telecommunication Technologies, 2009
Parallelized crowding scheme using a new interconnection model
P. K. Nanda, D. P. Muni, P. Kanungo
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2002

RECENT SCHOLAR PUBLICATIONS

Non-Uniform Illumination Image Thresholding based on K-Means Clustering and MLR
PK T Pattnaik
2025 International Conference (IC-CGU) , 2026
2026
Non-Uniform Illumination Image Thresholding Using MLP
T Pattnaik, P Kanungo
2025 4th International Conference on Range Technology (ICORT), 1-6 , 2025
2025
Brain tumor segmentation using DeepAttRes-Unet based transfer learning
P Priyadarshini, S Parija, P Kanungo, P Kumar Sahoo, T Kar
IET Conference Proceedings CP920 2025 (7), 1300-1305 , 2025
2025
Role of 5G Network in Smart Cities Toward Green Technology
Y Moukabaa, S Parija, P Kanungo
5G Green Communication Networks for Smart Cities, 1-15 , 2025
2025
Citations: 2
Advanced Diagnostic Framework with Vision Transformer for Multiclass Skin Disease Classification
PKRCB Barunaditya Mohanty, Ayush Singhal, Brajesh Kumar, Praveen Kumar Yadav
Computational Intelligence in Pattern Recognition. CIPR 2024 1152, 467-480 , 2025
2025
Retraction Note: An improved and low-complexity neural network model for curved lane detection of autonomous driving system
S Ghanem, P Kanungo, G Panda, P Parwekar
Soft Computing 28 (Suppl 2), 1031-1031 , 2024
2024
Camouflaged object detection using hybrid-deep learning model.
PKSS Padhy, I., J, T.S.C.M.R., CH, V.K.R.
Multimed Tools Appl. , 2024
2024
Citations: 4
An efficient low complex-functional link artificial neural network-based framework for uneven light image thresholding
T Pattnaik, P Kanungo, PK Sahoo, T Kar, P Jain, MS Soliman, MT Islam
IEEE Access 12, 118315-118338 , 2024
2024
Citations: 22
Multiclass Classification of Camouflage Images Using Combined WLD and LPQ Feature Set Using a ANN Classifier
I Padhy, P Kanungo, S Sahoo
International Conference on Advances in Signal Processing And Communication … , 2024
2024
Citations: 1
Video shot-boundary detection: issues, challenges and solutions
T Kar, P Kanungo, SN Mohanty, S Groppe, J Groppe
Artificial Intelligence Review 57 (4), 104 , 2024
2024
Citations: 33
Advanced Diagnostic Framework with Vision Transformer for Multiclass Skin Disease Classification
B Mohanty, A Singhal, B Kumar, PK Yadav, P Kanungo, RC Barik
International Conference on Computational Intelligence in Pattern … , 2024
2024
Multigrade Brain tumor classification in MRI images using Fine tuned EfficientNet
P Priyadarshini, Priyadarshi-Kanungo, Tejaswini-Kar
e-Prime - Advances in Electrical Engineering, Electronics and Energy, 100498 , 2024
2024
Citations: 63
Multiple Linear Regression based Illumination Normalization for Non-uniform Light Image Thresholding
T Pattnaik, P Kanungo, T Kar, PK Sahoo
e-Prime - Advances in Electrical Engineering, Electronics and Energy 7, 100411 , 2024
2024
Citations: 8
Predominant musical instrument detection using ensemble learning
S Pal, T Kar, P Kanungo
2024 International Conference on Emerging Systems and Intelligent Computing … , 2024
2024
Composer Identification in Classical Genre
S Pal, T Kar, P Kanungo, T Pattnaik
2023 IEEE 3rd International Conference on Applied Electromagnetics, Signal … , 2023
2023
Lane detection under artificial colored light in tunnels and on highways: an IoT-based framework for smart city infrastructure
S Ghanem, P Kanungo, G Panda, SC Satapathy, R Sharma
Complex & Intelligent Systems 9 (4), 3601-3612 , 2023
2023
Citations: 92
Brain tumor detection and classification from MRI images using cascaded deep neural networks
P Priyadarshini, AKM Khairuzzaman, P Kanungo
Microelectronics, Circuits and Systems: Select Proceedings of Micro2021, 301-311 , 2023
2023
Citations: 7
A YCbCr Model Based Shadow Detection and Removal Approach On Camouflaged Images
I Padhy, P Kanungo, S Sahoo
2022 OITS International Conference on Information Technology (OCIT) , 2023
2023
Citations: 3
RETRACTED ARTICLE: An improved and low-complexity neural network model for curved lane detection of autonomous driving system: S. Ghanem et al.
S Ghanem, P Kanungo, G Panda, P Parwekar
Soft Computing 27 (1), 493-504 , 2023
2023
Citations: 18
Customized YOLOv3 model for face detection in crowded images
Y Al Othmani, P Kanungo, S Ghanem, AA Alnaeb
2022 6th International Conference On Computing, Communication, Control And … , 2022
2022
Citations: 1

MOST CITED SCHOLAR PUBLICATIONS

Performance analysis of AODV, DSR, OLSR and DSDV routing protocols using NS2 Simulator
S Mohapatra, P Kanungo
Procedia Engineering 30, 69-76 , 2012
2012.0
Citations: 329
Lane detection under artificial colored light in tunnels and on highways: an IoT-based framework for smart city infrastructure
S Ghanem, P Kanungo, G Panda, SC Satapathy, R Sharma
Complex & Intelligent Systems 9 (4), 3601-3612 , 2023
2023.0
Citations: 92
Multigrade Brain tumor classification in MRI images using Fine tuned EfficientNet
P Priyadarshini, Priyadarshi-Kanungo, Tejaswini-Kar
e-Prime - Advances in Electrical Engineering, Electronics and Energy, 100498 , 2024
2024.0
Citations: 63
Image segmentation using thresholding and genetic algorithm
P Kanungo, PK Nanda, UC Samal
NIT, Rourkela, India , 2006
2006.0
Citations: 34
Video shot-boundary detection: issues, challenges and solutions
T Kar, P Kanungo, SN Mohanty, S Groppe, J Groppe
Artificial Intelligence Review 57 (4), 104 , 2024
2024.0
Citations: 33
Lane detection under artificial colored light in tunnels and on highways: an IoT-based framework for smart city infrastructure. Complex Intell. Syst.(2021)
S Ghanem, P Kanungo, G Panda
Citations: 33
A motion and illumination resilient framework for automatic shot boundary detection
TKP Kanungo
Signal, Image and Video Processing 11 (7), 1237-1244 , 2017
2017.0
Citations: 28
Comparative performance analysis of MANET routing protocols using nS2 simulator
S Mohapatra, P Kanungo
International Conference on Computational Intelligence and Information … , 2011
2011.0
Citations: 26
Parallel genetic algorithm based adaptive thresholding for image segmentation under uneven lighting conditions
P Kanungo, PK Nanda, A Ghosh
2010 IEEE International Conference on Systems, Man and Cybernetics, 1904-1911 , 2010
2010.0
Citations: 23
An efficient low complex-functional link artificial neural network-based framework for uneven light image thresholding
T Pattnaik, P Kanungo, PK Sahoo, T Kar, P Jain, MS Soliman, MT Islam
IEEE Access 12, 118315-118338 , 2024
2024.0
Citations: 22
Neighbourhood decision based impulse noise filter
AK Samantaray, P Kanungo, B Mohanty
IET Image Processing 12 (7), 1222-1227 , 2018
2018.0
Citations: 20
RETRACTED ARTICLE: An improved and low-complexity neural network model for curved lane detection of autonomous driving system: S. Ghanem et al.
S Ghanem, P Kanungo, G Panda, P Parwekar
Soft Computing 27 (1), 493-504 , 2023
2023.0
Citations: 18
Classification of objects and background using parallel genetic algorithm based clustering
P Kanungo, PK Nanda, A Ghosh
ELCVIA Electronic Letters on Computer Vision and Image Analysis 6 (3), 42-53 , 2007
2007.0
Citations: 18
Entropy feature and peak-means clustering based slowly moving object detection in head and shoulder video sequences
PK Sahoo, P Kanungo, S Mishara, BP Mohanty
Journal of King Saud University - Computer and Information Sciences , 2021
2021.0
Citations: 17
Face Recognition from Partial Face Data
S Alfattama, P Kanungo, SK Bisoy
2021 International Conference in Advances in Power, Signal, and Information … , 2021
2021.0
Citations: 16
A fast valley-based segmentation for detection of slowly moving objects
PK Sahoo, P Kanungo, S Mishra
Signal, Image and Video Processing 12 (7), 1265-1272 , 2018
2018.0
Citations: 16
Parallelized crowding scheme using a new interconnection model
PK Nanda, DP Muni, P Kanungo
AFSS International Conference on Fuzzy Systems, 436-443 , 2002
2002.0
Citations: 13
GMM Based Adaptive Thresholding for Uneven Lighting Image Binarization
T Pattnaik, P Kanungo
Journal of Signal Processing Systems , 2021
2021.0
Citations: 12
Motion and illumination defiant cut detection based on Weber features
T Kar, P Kanungo
IET Image processing 12 (10), 1903-1912 , 2018
2018.0
Citations: 12
A texture based method for scene change detection
T Kar, P Kanungo
2015 IEEE Power, Communication and Information Technology Conference (PCITC … , 2015
2015.0
Citations: 11

Priyadarshi Kanungo

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Scopus Publications

RECENT SCHOLAR PUBLICATIONS

MOST CITED SCHOLAR PUBLICATIONS

INDUSTRY EXPERIENCE