Kantilal Rane

Scopus Publications

A Comparative Evaluation of Deep Learning Architectures for Prostate Cancer Segmentation: Introducing TrionixNet with N-Core Multi-Attention Mechanism
Yogendra Narayan, Davinder Paul Singh, Tathagat Banerjee, Pawandeep Kour, Kantilal Rane, Anand Deva Durai C, K. Punnam Chandar, Rajanish Kumar Kaushal, Ram Murat Singh, Yuvika Dhillon
Archives of Computational Methods in Engineering, 2026
Information Extraction with the Optimized Selective Kernel-Based Deep Learning from the Unstructured Invoice
Prasad Dilip Kulkarni, Vijay Deshmukh, Kantilal Pitambar Rane
New Generation Computing, 2026
Closed-loop digital twin intelligence for resilient and autonomous optical infrastructure and communications
Swati Patil, Dayanand Bhaurao Jadhav, Kantilal Rane, Hemant A Wani
Journal of Optical Communications, 2026
Ultra-reliable optical communication links are required for mission-critical applications such as 5G/6G fronthaul, industrial automation, and data-center interconnects. In these applications the rare events that lead to communication failures are the limiting factor, rather than average performance. This work introduces a Monte-Carlo-driven digital twin framework for reliably designing coherent single-mode fiber optical links using Monte-Carlo simulation methods to compute outage probability for the given link parameters. The optical propagation is modeled using the nonlinear Schrödinger equation and solved using the Split-Step Fourier Method. The model incorporates chromatic dispersion, Kerr nonlinearity, attenuation, and variations in the noise statistics in the environment. Outage probability is defined as P out = Pr⁡( Q < Q th ), where Q -factor is estimated via Monte-Carlo sampling. To reduce the computational cost of rare-event sampling, a neural-network surrogate digital twin is trained to model the relationship between link parameters, noise statistics, and outage probability. The fidelity of the model is assessed using MAE and R 2 metrics. The multi-objective optimization problem of maximizing outage probability while minimizing transmit power is solved using Pareto optimality principles. The results show a dramatic reduction in outage probability compared to designs based on fixed margins while providing a speedup of over two orders-of-magnitude compared to brute-force Monte-Carlo SSFM simulations. All simulations and models are available in an open-source and reproducible Python framework.
The role of robotics in smart agriculture for sustainability of food systems
Bhiksha Gugulothu, Murugesan Ganesan, Mohd Naved, D. Vetrithangam, Kantilal Pitambar Rane, Manisha Mali
Robotics and Intelligent Machines in Smart Agriculture Emerging Systems and Applications, 2026
The increasingly pressing need for food supply in the face of labor shortage, climate change, and sustainability has stimulated the adoption of new technology and machinery for agriculture. As a fundamental factor for smart agriculture, robotics enables the transformation of automation of farming activities and can be used to improve the productivity and sustainability of crop production. From self-driving tractors and robot harvesters to drones and weeding robots, robotics has been changing agriculture by cutting resource use, boosting yield, and reducing reliance on human labor. This chapter further investigates the adoption of robotics in precision agriculture, studying pivotal applications, namely, crop monitoring, sowing, watering, spraying, harvesting, and the supply chain. It also discusses the enabling technologies, such as AI, IoT, and computer vision, that collaborate with robotics to improve agricultural decision-making. Some challenges, such as expensive implementation, interoperable problems, and ethical issues, are also discussed. Lastly, this chapter outlines the future and opportunities for robots to contribute to developing resilient, climate-smart, and fully automated farming ecosystems.
AI-synergistic effect in C-RNN based online signature profiling and hash-QR encoding for forge signature detection, documents protection and applications authentication
Hemant Wani, Kantilal P. Rane, Vijay M. Deshmukh, Kushal D. Badgujar, J. Jeyvel, Somnath Wategaonkar
Multimedia Tools and Applications, 2025
CLAHE-AlexNet optimized deep learning model for accurate detection of diabetic retinopathy
Swetha G., Gaurav Gupta, Kantilal Pitambar Rane, Omkar M. Ghag, Sachin K. Korde, Sachin Lalar, Batyrkhan Omarov, Abhishek Raghuvanshi
Bulletin of Electrical Engineering and Informatics, 2025
Diabetic retinopathy (DR) is a disease that affects the blood vessels that are located in the retina. Loss of vision due to diabetes is a common consequence of the illness and a key factor in the progression of vision loss and blindness. Both ophthalmology and diabetes research have become more dependent on computer vision and image processing techniques in recent years. Fundus photography, also known as a fundus image, is a method that may be used to capture an image of the back of a person's eye. This article presents optimized deep learning model for diagnostic marking in retinal fundus images towards accurate detection of retinopathy. For experimental work, 500 images were selected from available open source Kaggle data set. 400 images were used to train deep learning model and remaining 100 images were used to validate the model. Images were enhanced using the contrast limited adaptive histogram equalization (CLAHE) algorithm. Pre trained convolutional neural network (CNN) models-AlexNet, VGG16, GoogleNet, and ResNet are used for classification and prediction of images. Accuracy, specificity, precision and F1-score of AlexNet is better than VGG16, ResNet-50, and GoogleNet. Sensitivity of ResNet-50 is higher than other pre trained CNN models.
Optimized convolutional neural network enabled technique for sentiment analysis from social media data
Chinta Veena, Kavita A. Sultanpure, Meenakshi Meenakshi, Sunil L. Bangare, Punam Sunil Raskar, Shriram Sadashiv Kulkarni, Myla M. Arcinas, Kantilal Pitambar Rane
Bulletin of Electrical Engineering and Informatics, 2025
Sentiment analysis is an area of computational linguistics that studies natural language processing. The most significant subtasks are gathering people's thoughts and organizing them into groups to determine how they feel. The primary purpose of sentiment analysis is to determine whether the individual who created a piece of material has a positive or negative opinion about a subject. It has been claimed that sentiment analysis and social media mining have contributed to the recent success of both private sector and the government. Emotional analysis has applications in practically every aspect of modern life, from individuals to corporations, telecommunications to medical, and economics to politics. This article describes an improved sentiment analysis model based on gray level co-occurrence matrix (GLCM) texture feature extraction and a convolutional neural network (CNN). This model was created using tweets. First, texture characteristics are extracted from the input data set using the GLCM technique. This feature extraction improves categorization accuracy. CNNs are used to classify objects. It outperforms both the support vector machine and the AdaBoost algorithms in terms of accuracy. CNN has achieved an accuracy of 98.5% for sentiment analysis task.
AI-Driven Intelligent Visual Analytics of Remote-Sensed Data for Sustainable Earth and Environmental Monitoring
R Vignesh, Vivek Parashar, Gayatri Hegde, Ravi Veluri, Nusrat Parveen, Mutkule Raghunath, Sandipan Biswas, Kantilal Rane, Abhishek Raghuvanshi
Journal of Applied Science and Technology Trends, 2025
The ecosystem degradation and climate change are increasing at a very high rate, and this phenomenon must be monitored with the aid of the most advanced technologies to organize the management of resources in the most efficient manner. In the paper, a smart visual analytics system is proposed that may be applied to utilize the remote-sensed data on the holistic monitoring of the environment. The model applies multispectral and hyperspectral satellite images and machine learning and deep learning models to determine crucial indicators of the environment (such as vegetation cover, water quality, and urban growth patterns). A graph-based clustering approach with Convolutional Neural Networks (CNNs) can be used to extract features and cluster data to identify anomalies in real time to interpret geospatial data on a big scale. The results show that the specified system would be effective in the land cover classification with an accuracy of 93%, in contrast to the accuracy of the conventional remote sensing analytics tools, which is 15 percent higher. In addition, the use of normalized different indexes estimation of water quality led to the R² of 0.87 that indicated the high predictive reliability. The visual analytics dashboard can dynamically interact with spatial-temporal patterns in such a way that the sustainability of the available resources can be managed by the decision-making process.
An efficient course recommendation system for higher education students using machine learning techniques
Myla M. Arcinas, Meenakshi Meenakshi, Pranjali S. Bahalkar, Deepali Bhaturkar, Sachin Lalar, Kantilal Pitambar Rane, Shaifali Garg, Batyrkhan Omarov, Abhishek Raghuvanshi
Bulletin of Electrical Engineering and Informatics, 2025
Education institutions and teachers are in desperate need of automated, non-intrusive means of getting student feedback that would allow them to better understand the learning cycle and assess the success of course design. Students would benefit from a framework that intelligently guides their actions and provides exercises or resources to support and enhance their learning. The recommender system framework is a software agent that learns the user's preferences through a variety of channels and then utilizes that knowledge to provide product suggestions. A recommendation engine considers all potential user interests as background information, uses that knowledge to produce convincing recommendations, and then returns those ideas to the user. This article presents a feature selection and machine learning based course recommendation system for higher education students. principal component analysis (PCA) algorithm is used for feature selection. AdaBoost, k nearest neighbour (KNN), and Naïve Bayes algorithms are used to classify and predict student data. It is found that the AdaBoost algorithm is having better accuracy and F1 score for course recommendation to students. PCA AdaBoost is achieving an accuracy of 99.5%.
Explainable AI for inverse-design of optical network on chip routers
Jotiram K. Deshmukh, Kantilal Pitambar Rane, Milind P. Gajare, Monali Chaudhari
Journal of Optical Communications, 2025
Inverse design uses advanced AI capabilities to autonomously create the best geometries and configurations for an optical network-on-chip router. Here, we use reinforcement learning to facilitate the design process, where the system learns over time what architectures best suit the target criteria (latency, signal loss, area, throughput) to achieve the best functioning router. However, while reinforcement learning is an effective means of achieving desired output, the reinforcement learning created is often complex and non-interpretable for human engineers. Therefore, we use explainable artificial intelligence methods to make the final interpretations more interpretable and justifiable. Explainable artificial intelligence helps to explain why each move was made during the design process. Thus, reinforcement learning-inverse-designed optical network-on-chip routers will perform better under desired metrics with explainable artificial intelligence providing human designers a level of explainability and justification for human trust and verification for artificial intelligence generated things.
An Empirical Research of AI Approaches in Electronic Engineering
V. Muralidharan, Kantilal Pitambar Rane, K. Rashmi, Rakesh Chandrashekar, Amandeep Nagpal, Purnendu Bikash Acharjee
Recent Trends in Engineering and Science for Resource Optimization and Sustainable Development, 2025
RETRACTED ARTICLE: Influence of grey wolf optimization feature selection on gradient boosting machine learning techniques for accurate detection of liver tumor (SN Applied Sciences, (2023), 5, 7, (178), 10.1007/s42452-023-05405-9)
Malik Jawarneh, José Luis Arias-Gonzáles, Dattatray P. Gandhmal, Rami Qays Malik, Kantilal Pitambar Rane, Batyrkhan Omarov, Cosmena Mahapatra, Mohammad Shabaz
Discover Applied Sciences, 2025
Internet of things and optimized knn based intelligent transportation system for traffic flow prediction in smart cities
Sunkara Teena Mrudula, Meenakshi, Mahyudin Ritonga, S. Sivakumar, Malik Jawarneh, Sammy F, T. Keerthika, Kantilal Pitambar Rane, Bhaskar Roy
Measurement Sensors, 2024
AA/AAO to Navigation: Cost Effective Rpi-Web-Server Based System with Autonomous/Add-On Mobile Applications for Road-Way Emergency Diversion Alert during Disastrous Situation
Ojal Rane, Kantilal Pitambar Rane
International Journal of Intelligent Transportation Systems Research, 2024
Exploring Heat Dynamics: Analyzing Turbine Blade Performance
Computational Optimization Modeling and Simulation for Engineering Applications, 2024
Circuit Vision: Fast and Efficient Digitization of Complex Hand-Drawn Circuit using Yolov8
Somnath Wategaonkar, Kantilal P. Rane, Tejeshree Bhoir, Komal Chaudhari, Prerna Bhopi, Sanesh Akhade
Icdcs 2024 2024 7th International Conference on Devices Circuits and Systems, 2024
Railway Ticket Scanner using Optical Character Recognition (OCR) and QR Code Generation for Waiting List Ticket Allotment
Anand Sutar, Kantilal Rane, Kamble Tejas Shankar, Jadhav Sahil Sanjay, Karale Aniket Kisan, Katkar Yash Mahesh
Indiscon 2024 5th IEEE India Council International Subsections Conference Science Technology and Society, 2024
Low-Cost, High-Speed Hybrid Solar Powered Auto Geared Electric Bicycle
Anand Sutar, Kantilal Rane, Swati Mahamuni, Tanushree Sarkar, Moon Banerjee, B Lakshmana Swamy
7th International Conference on Inventive Computation Technologies Icict 2024, 2024
Development and Execution of an IoT-Based Accident Detection and Alert System with Location Tracking
Somnath R. Wategonkar, Kantilal P. Rane, Surekha A. Khot, Navin Ashok Yadav, Saish Anand Vilankar, Shyam Akashe
Proceedings 2024 6th International Conference on Computational Intelligence and Communication Technologies Ccict 2024, 2024
IoT device type identification using training deep quantum neural networks optimized with a chimp optimization algorithm for enhancing IoT security
C.P. Shirley, Jaydip Kumar, Kantilal Pitambar Rane, Narendra Kumar, Deevi Radha Rani, Kuntamukkula Harshitha, Mohit Tiwari
Journal of High Speed Networks, 2024
Internet of things driven multilinear regression technique for fertilizer recommendation for precision agriculture
Praveen Kumar Kollu, Manoj L. Bangare, P. Venkata Hari Prasad, Pushpa M. Bangare, Kantilal Pitambar Rane, José Luis Arias-Gonzáles, Sachin Lalar, Mohammad Shabaz
SN Applied Sciences, 2023
Machine learning and Sensor Based Multi Robot System with Voice Recognition for Assisting the Visually Impaired
Shirley C P, Kantilal Rane, Kolli Himantha Rao, Bradley Bright B, Prashant Agrawal, Neelam Rawat
Journal of Machine and Computing, 2023
An IoT-Based System for Managing and Monitoring Smart Irrigation through Mobile Integration
Senthil Vadivu M, Purushotham Reddy M, Kantilal Rane, Narendra Kumar, Karthikayen A, Nitesh Behare
Journal of Machine and Computing, 2023
Retraction:Influence of grey wolf optimization feature selection on gradient boosting machine learning techniques for accurate detection of liver tumor
Malik Jawarneh, José Luis Arias-Gonzáles, Dattatray P. Gandhmal, Rami Qays Malik, Kantilal Pitambar Rane, Batyrkhan Omarov, Cosmena Mahapatra, Mohammad Shabaz
SN Applied Sciences, 2023
A Framework for Providing Structured Invoice Document using Optimized Bert Enabled Deep Convolutional Neural Network Classifier
Prasad Dilip Kulkarni, Vijay Deshmukh, Kantilal Pitambar Rane
7th International Conference on I Smac Iot in Social Mobile Analytics and Cloud I Smac 2023 Proceedings, 2023
Intelligent Motorbike Helmets: Sensor-Driven Speed Regulation and Safety Enhancement for Motorcyclists
Shekhar Mane, Kantilal Rane, Zunzarrao Thorat, Tukaram Sawant, Mahesh Bulhe
Proceedings International Conference on Technological Advancements in Computational Sciences Ictacs 2023, 2023
Design of Phase Array Antenna for Enhanced Performance in 5G Communication Systems
J. Jeyavel, Kantilal Rane, Shekhar M. Mane, Suraj Thakur, Arman Shaikh
Proceedings International Conference on Technological Advancements in Computational Sciences Ictacs 2023, 2023
Towards applicability of blockchain in agriculture sector
Guna Sekhar Sajja, Kantilal Pitambar Rane, Khongdet Phasinam, Thanwamas Kassanuk, Ethelbert Okoronkwo, P. Prabhu
Materials Today Proceedings, 2023
Tuning and Sensitivity Improvement of Bi-Metallic Structure-Based Surface Plasmon Resonance Biosensor with 2-D ε -Tin Selenide Nanosheets
Natarajan Sathya, Bhishma Karki, Kantilal Pitambar Rane, Ankit Jha, Amrindra Pal
Plasmonics, 2022
Intelligent gravitational search random forest algorithm for fake news detection
Rathika Natarajan, Abolfazl Mehbodniya, Kantilal Pitambar Rane, Sonika Jindal, Mohammed Faez Hasan, Luis Vives, Abhishek Bhatt
International Journal of Modern Physics C, 2022
Quantum-inspired meta-heuristic algorithms with deep learning for facial expression recognition under varying yaw angles
Abhishek Bhatt, Tanweer Alam, Kantilal Pitambar Rane, Rainu Nandal, Meenakshi Malik, Rahul Neware, Samiksha Goel
International Journal of Modern Physics C, 2022
Quantum-inspired firefly algorithm integrated with cuckoo search for optimal path planning
Harish Kundra, Wasim Khan, Meenakshi Malik, Kantilal Pitambar Rane, Rahul Neware, Vishal Jain
International Journal of Modern Physics C, 2022
An Investigation of the MIMO Space Time Block Code Based Selective Decode and Forward Relaying Network over η–µ Fading Channel Conditions
Ravi Shankar, V. V. Raghava Raman, Kantilal Pitamber Rane, Sarojini B. K., Rahul Neware
Journal of Telecommunications and Information Technology, 2022
Blockchain-Based Secure Mengers Authentication for Industrial IoT
Shashidhar Sonnad, Mohan Awasthy, Kantilal Rane, Moon Banerjee, Dharam Buddhi, Bhasker Pant
Proceedings of the 2022 11th International Conference on System Modeling and Advancement in Research Trends Smart 2022, 2022
Photocatalytic Activity of Green Construction TiO2Nanoparticles from Phyllanthus niruri Leaf Extract
Annin K. Shimi, Saikh Mohammad Wabaidur, Masoom Raza Siddiqui, Md Ataul Islam, Kantilal Pitamber Rane, T. S. Arul Jeevan
Journal of Nanomaterials, 2022
Optimized Feature Selection and Image Processing Based Machine Learning Technique for Lung Cancer Detection
Dr. P. Nancy, S Ravi Kishan, Kantilal Pitambar Rane, Dr. Karthikeyan Kaliyaperumal, Dr. Meenakshi, I Kadek Suartama
International Journal of Electrical and Electronics Research, 2022
Deep Neural Network-Based Novel Mathematical Model for 3D Brain Tumor Segmentation
Ajay S. Ladkat, Sunil L. Bangare, Vishal Jagota, Sumaya Sanober, Shehab Mohamed Beram, Kantilal Rane, Bhupesh Kumar Singh
Computational Intelligence and Neuroscience, 2022
Machine Learning and Artificial Intelligence in the Food Industry: A Sustainable Approach
Rajnish Kler, Ghada Elkady, Kantilal Rane, Abha Singh, Md Shamim Hossain, Dheeraj Malhotra, Samrat Ray, Komal Kumar Bhatia
Journal of Food Quality, 2022
Performance of Machine Learning and Image Processing in Plant Leaf Disease Detection
Abu Sarwar Zamani, L. Anand, Kantilal Pitambar Rane, P. Prabhu, Ahmed Mateen Buttar, Harikumar Pallathadka, Abhishek Raghuvanshi, Betty Nokobi Dugbakie
Journal of Food Quality, 2022
Development of Machine Learning and Medical Enabled Multimodal for Segmentation and Classification of Brain Tumor Using MRI Images
L. Anand, Kantilal Pitambar Rane, Laxmi A. Bewoor, Jyoti L. Bangare, Jyoti Surve, Mutkule Prasad Raghunath, K. Sakthidasan Sankaran, Bernard Osei
Computational Intelligence and Neuroscience, 2022
Synthesis and Applications of Green Synthesized TiO2Nanoparticles for Photocatalytic Dye Degradation and Antibacterial Activity
Annin K. Shimi, Hiwa M. Ahmed, Muhammad Wahab, Snehlata Katheria, Saikh Mohammad Wabaidur, Gaber E. Eldesoky, Md Ataul Islam, Kantilal Pitamber Rane
Journal of Nanomaterials, 2022
The construction of shower maximising sensitive MCP detector
Kushal D Badgujar, N B V SUBRHMANYAM, Prabhat Munshi, K P Rane, Lalit Mohan Pant, B K Nayak
Pramana Journal of Physics, 2021
Research on vibration monitoring and fault diagnosis of rotating machinery based on internet of things technology
Xiaoran Zhang, Kantilal Pitambar Rane, Ismail Kakaravada, Mohammad Shabaz
Nonlinear Engineering, 2021
Smartphone-Based mHealth and Internet of Things for Diabetes Control and Self-Management
Abolfazl Mehbodniya, A. Suresh Kumar, Kantilal Pitambar Rane, Komal Kumar Bhatia, Bhupesh Kumar Singh
Journal of Healthcare Engineering, 2021
RETRACTED: Financial Fraud Detection in Healthcare Using Machine Learning and Deep Learning Techniques
Abolfazl Mehbodniya, Izhar Alam, Sagar Pande, Rahul Neware, Kantilal Pitambar Rane, Mohammad Shabaz, Mangena Venu Madhavan
Security and Communication Networks, 2021
An Enhanced Secure Deep Learning Algorithm for Fraud Detection in Wireless Communication
Sumaya Sanober, Izhar Alam, Sagar Pande, Farrukh Arslan, Kantilal Pitambar Rane, Bhupesh Kumar Singh, Aditya Khamparia, Mohammad Shabaz
Wireless Communications and Mobile Computing, 2021
Design of issuing and self-returning modules for library books for mega campus by using arm 7 web-server and cloud
International Journal of Scientific and Technology Research, 2020
Symbolic-OTP based security system for domestic use
International Journal of Scientific and Technology Research, 2020
Diabetic retinopathy detection and grading using machine learning
Kirange D.K. and
International Journal of Advanced Trends in Computer Science and Engineering, 2019
Intelligent bus stand monitoring and control
Shital M. Dharrao, Vijay D. Choudhary, Kantilal P. Rane
ACM International Conference Proceeding Series, 2016
Video manipulation using frames estimation through mosaic creation
Kantilal Rane, Sunil Bhirud
Advances in Intelligent and Soft Computing, 2012
Online signature classification using modified fuzzy min-max neural network with compensatory neuron topology
B. M. Chaudhari, Rupal S. Patil, K. P. Rane, Ulhas B. Shinde
Communications in Computer and Information Science, 2010

MOST CITED SCHOLAR PUBLICATIONS

Research on vibration monitoring and fault diagnosis of rotating machinery based on internet of things technology
X Zhang, KP Rane, I Kakaravada, M Shabaz
Nonlinear Engineering 10 (1), 245-254 , 2021
2021
Citations: 190
Performance of Machine Learning and Image Processing in Plant Leaf Disease Detection
AS Zamani, L Anand, KP Rane, P Prabhu, AM Buttar, H Pallathadka, ...
Journal of Food Quality 2022 (1), 1598796 , 2022
2022
Citations: 169
An enhanced secure deep learning algorithm for fraud detection in wireless communication
S Sanober, I Alam, S Pande, F Arslan, KP Rane, BK Singh, A Khamparia, ...
Wireless Communications and Mobile Computing 2021 (1), 6079582 , 2021
2021
Citations: 144
Financial Fraud Detection in Healthcare Using Machine Learning and Deep Learning Techniques
A Mehbodniya, I Alam, S Pande, R Neware, KP Rane, M Shabaz, ...
Security and Communication Networks 2021 (1), 9293877 , 2021
2021
Citations: 138
Towards applicability of blockchain in agriculture sector
GS Sajja, KP Rane, K Phasinam, T Kassanuk, E Okoronkwo, P Prabhu
Materials Today: Proceedings 80, 3705-3708 , 2023
2023
Citations: 131
Synthesis and Applications of Green Synthesized TiO 2 Nanoparticles for Photocatalytic Dye Degradation and Antibacterial Activity
AK Shimi, HM Ahmed, M Wahab, S Katheria, SM Wabaidur, GE Eldesoky, ...
Journal of Nanomaterials 2022 (1), 7060388 , 2022
2022
Citations: 121
Machine Learning and Artificial Intelligence in the Food Industry: A Sustainable Approach
R Kler, G Elkady, K Rane, A Singh, MS Hossain, D Malhotra, S Ray, ...
Journal of Food Quality 2022 (1), 8521236 , 2022
2022
Citations: 91
Vehicle tracking, monitoring and alerting system: a review
SS Dukare, DA Patil, KP Rane
International Journal of Computer Applications 119 (10), 39-44 , 2015
2015
Citations: 60
Quantum-inspired firefly algorithm integrated with cuckoo search for optimal path planning
H Kundra, W Khan, M Malik, KP Rane, R Neware, V Jain
International Journal of Modern Physics C 33 (02), 2250018 , 2022
2022
Citations: 52
Literature Survey on Door Lock Security Systems
KPR Pradnya R. Nehete, J. P. Chaudhari, S. R. Pachpande
International Journal of Computer Applications 153 (2), 13-18 , 2016
2016
Citations: 48
Deep Neural Network‐Based Novel Mathematical Model for 3D Brain Tumor Segmentation
AS Ladkat, SL Bangare, V Jagota, S Sanober, SM Beram, K Rane, ...
Computational Intelligence and Neuroscience 2022 (1), 4271711 , 2022
2022
Citations: 43
Tuning and Sensitivity Improvement of Bi-Metallic Structure-Based Surface Plasmon Resonance Biosensor with 2-D -Tin Selenide Nanosheets
N Sathya, B Karki, KP Rane, A Jha, A Pal
Plasmonics 17 (3), 1001-1008 , 2022
2022
Citations: 42
Design and development of low cost humanoid robot with thermal temperature scanner for COVID-19 virus preliminary identification
KP Rane
International Journal 9 (3), 3485-3493 , 2020
2020
Citations: 37
Development of machine learning and medical enabled multimodal for segmentation and classification of brain tumor using MRI images
L Anand, KP Rane, LA Bewoor, JL Bangare, J Surve, MP Raghunath, ...
Computational intelligence and neuroscience 2022 (1), 7797094 , 2022
2022
Citations: 35
A comparative evaluation of deep learning architectures for prostate cancer segmentation: Introducing TrionixNet with N-core multi-attention mechanism
Y Narayan, DP Singh, T Banerjee, P Kour, K Rane, ADD C, KP Chandar, ...
Archives of Computational Methods in Engineering, 1-40 , 2025
2025
Citations: 33
Smartphone‐Based mHealth and Internet of Things for Diabetes Control and Self‐Management
A Mehbodniya, A Suresh Kumar, KP Rane, KK Bhatia, BK Singh
Journal of Healthcare Engineering 2021 (1), 2116647 , 2021
2021
Citations: 31
Internet of things and optimized knn based intelligent transportation system for traffic flow prediction in smart cities
ST Mrudula, M Ritonga, S Sivakumar, M Jawarneh, T Keerthika, KP Rane, ...
Measurement: Sensors 35, 101297 , 2024
2024
Citations: 28
Intelligent gravitational search random forest algorithm for fake news detection
R Natarajan, A Mehbodniya, KP Rane, S Jindal, MF Hasan, L Vives, ...
International Journal of Modern Physics C 33 (06), 2250084 , 2022
2022
Citations: 28
Internet of things driven multilinear regression technique for fertilizer recommendation for precision agriculture
PK Kollu, ML Bangare, PV Hari Prasad, PM Bangare, KP Rane, ...
SN Applied Sciences 5 (10), 264 , 2023
2023
Citations: 25
Diabetic retinopathy detection and grading using machine learning
DK Kirange, JP Chaudhari, KP Rane, KS Bhagat, N Chaudhri
Int. J. of Adv. Trends in Comput. Sci. & Engine 8 (6), 3570-3576 , 2019
2019
Citations: 23

Kantilal Rane

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Scopus Publications

RECENT SCHOLAR PUBLICATIONS

MOST CITED SCHOLAR PUBLICATIONS