KARTHIKEYAN M P

@rmkec.ac.in

Assistant Professor - Computer Science and Engineering
R. M. K. Engineering College

KARTHIKEYAN M P


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https://researchid.co/karthikeyan.m.p

EDUCATION

B.E., M.Tech., (

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Artificial Intelligence, Computer Engineering
15

Scopus Publications

36

Scholar Citations

3

Scholar h-index

Scopus Publications

  • Exploring the Various Machine Learning Models for Image Generation - A Comprehensive Survey Unlocking the Future of Digital Creativity
    M. Balasubramanian, M. Naveen Joel, M. P. Karthikeyan
    Communications in Computer and Information Science, 2026
  • Automated Detection Model (ADM) for Glaucoma, Exudate and Diabetic Retinopathy (DR) Diagnosis Using Fundus Images
    M P Karthikeyan, E.A. Mary Anita, D. Mohana Geetha
    2nd International Conference on Research Methodologies in Knowledge Management Artificial Intelligence and Telecommunication Engineering Rmkmate 2025, 2025
    A total of 15 million people in India suffer from blindness yet statistical analysis shows 75% of these cases can be treated. The research shows DR and Glaucoma lead to blindness in India. Long-term diabetes mainly causes diabetic retinopathy which stands as the primary cause of blindness. Glaucoma damages the optic nerve until blindness develops. The digitized format of fundus images provides useful diagnostic information about infected retinas for proper eye disease detection. Eye defect diagnosis at an early stage enables medical care that greatly decreases patient vision loss risk. An ophthalmologist conducted the disease screening process through examination of fundus image abnormalities. Higher rates of DR and glaucoma prevalence do not affect the number of available ophthalmologists for evaluating fundus images so the prevention of diseases has been delayed. An automated analytical system should be developed presently to help ophthalmologists enhance their diagnostic process efficiency. The paper introduces an artificial learning methodology that utilizes concatenate systems to detect input fundus images in three categories namely ND and GI and EI and DRI. No Diseases (ND), ii. Glaucoma (GI) iii. The classification groups include Exudate infected Images (EI) along with two other categories namely Glaucoma (GI) and DR Images (DRI). The proposed model Automated Detection Model (ADM) starts by analyzing input samples with histogram-based model and employs DenseNet121 and Inception-ResNetV2to facilitate further processing. The Convolution Neural Networks (CNN) function gathers and sorts the feature extraction data obtained from both models. The proposed approach demonstrates improved accuracy and recall plus average precision when used instead of a solitary model. The proposed machine-learning approach using fundus images proves successful for Glaucoma, Exudate and DR diagnosis according to this experiment.
  • Track Damage And Obstacle Detection Using Multi Sensor Fusion Framework
    S.Padma Priya, P S Abarna, C.Manjula Devi, S Shahul Hammed, M.P. Karthikeyan, K.Muthu Saravanan
    2024 15th International Conference on Computing Communication and Networking Technologies Icccnt 2024, 2024
    The integration of Internet of Things (IoT) technology into railway track monitoring systems marks a pivotal advancement in ensuring the safety and efficiency of railway operations. Through strategic deployment of sensors along the tracks, this innovative system offers real-time detection of obstacles, furnishing vital data for timely intervention to avert potential accidents. This capability not only elevates passenger and crew safety but also bolsters the reliability of railway transportation systems as a whole. The system constantly scans the track ahead of the train for any anomalies using sensors positioned toward the front of the vehicle. The system immediately notifies the application faults it detects, enabling prompt action. Additionally, it updates the status of an IoT platform and displays it for personnel on board via an LCD panel. An audio alarm is generated in the event of critical sensor readings to ensure prompt attention. By lowering potential risks and responding quickly to track problems, This IoT-based solution holds the promise of revolutionizing railway operations by furnishing augmented safety, efficiency, and reliability, thereby addressing the burgeoning demands of contemporary transportation infrastructure.
  • Control of Autonomous Underwater Vehicles
    M. P. Karthikeyan, S. Anitha Jebamani, P. Umaeswari, K. Chitti Babu, C. Geetha, S. Kirupavathi
    Artificial Intelligence for Autonomous Vehicles, 2024
    In recent years, increasing the level of autonomy that underwater vehicles are capable of operating on their own has become a crucial component in order to cope with the highly dangerous and alien environment of the ocean. This is because the ocean is a totally different environment from land. This is due to the fact that the environment of the ocean is unfamiliar as well as lethal. Nowadays, autonomous underwater vehicles, also known as AUVs, are largely chosen over remotely operated vehicles, also known as ROVs, for the majority of the jobs that need engagement with the underwater environment. This is done to prevent the operators from becoming exhausted and to increase the likelihood that they will remain safe. Research on ocean resources, oceanographic mapping, inspections of deep-sea pipelines, and other activities of a similar kind made up the majority of the work linked with underwater intervention. In these kinds of applications, having precise control over an AUV's location of the greatest importance if one wishes to gather data of the best possible quality. This is because the precision with which the AUV maintains its station and records its location is a crucial role in influencing the quality of the data that are acquired. This is the reason why this is the case. On the other hand, achieving precise trajectory tracking control of an AUV is an extremely challenging task. This is owing to the unstructured nature of the undersea environment as well as the fact that vehicle dynamics is extremely nonlinear, coupled, and time-varying. Additionally, this is a result of the fact that the vehicle is moving. In addition to these, changes in the hydrodynamic coefficients, which are induced by changing operating conditions and vehicle, may be vulnerable to unknown variables such as ocean currents, which make the design of the trajectory tracking control much more difficult. Changes in the hydrodynamic coefficients are induced by changing operating conditions and vehicle. Because of this, it is of utmost importance to have a tracking control system for an AUV that is built to accommodate the unpredictability of the marine environment. In order to carry out nontrivial autonomous operations in the deep sea, specifically those that are in regions that are inaccessible to humans, it is necessary to have a manipulator arm that is affixed to the underwater vehicle. The issue is made more complex to tackle as a result of these elements working together. As a direct result of the connected manipulator arm, the auxiliary undersea vehicle maintenance system (AUVMS) transforms into a structurally redundant example of kinematic redundancy. As a direct result of this, it is necessary to put into action various strategies for the resolution of redundancy. The task space-based control scheme design ideas have been offered as a possible remedy to the issue of redundancy resolution as part of the scope of this research project.
  • Towards developing an automated technique for glaucomatous image classification and diagnosis (AT-GICD) using neural networks
    M. P. Karthikeyan, E. A. Mary Anita, D. Mohana Geetha
    International Journal of Information Technology Singapore, 2023
  • IM-EDRD from Retinal Fundus Images Using Multi-Level Classification Techniques
    M. P. Karthikeyan, E. A. Mary Anita
    Intelligent Automation and Soft Computing, 2023
    In recent years, there has been a significant increase in the number of people suffering from eye illnesses, which should be treated as soon as possible in order to avoid blindness. Retinal Fundus images are employed for this purpose, as well as for analysing eye abnormalities and diagnosing eye illnesses. Exudates can be recognised as bright lesions in fundus pictures, which can be the first indicator of diabetic retinopathy. With that in mind, the purpose of this work is to create an Integrated Model for Exudate and Diabetic Retinopathy Diagnosis (IM-EDRD) with multi-level classifications. The model uses Support Vector Machine (SVM)-based classification to separate normal and abnormal fundus images at the first level. The input pictures for SVM are pre-processed with Green Channel Extraction and the retrieved features are based on Gray Level Co-occurrence Matrix (GLCM). Furthermore, the presence of Exudate and Diabetic Retinopathy (DR) in fundus images is detected using the Adaptive Neuro Fuzzy Inference System (ANFIS) classifier at the second level of classification. Exudate detection, blood vessel extraction, and Optic Disc (OD) detection are all processed to achieve suitable results. Furthermore, the second level processing comprises Morphological Component Analysis (MCA) based image enhancement and object segmentation processes, as well as feature extraction for training the ANFIS classifier, to reliably diagnose DR. Furthermore, the findings reveal that the proposed model surpasses existing models in terms of accuracy, time efficiency, and precision rate with the lowest possible error rate.
  • Sign Language Recognition using Python and OpenCV
    Kandasamy S, Mowlieshwaran S, Kiran R, Kishore DS, Karthikeyan M
    Proceedings 2023 3rd International Conference on Smart Data Intelligence Icsmdi 2023, 2023
    Conversing with an individual along with listening to impairment is consistently a primary problem. Authorized foreign language has indelibly come to be the ultimate cure-all as well as is an extremely effective resource for people with listening and also pep talk impairment to communicate their emotions and points of view to the world. It generates a combination method between all of them as well as others that are softer and less sophisticated. Having said that, the creation of an authorized foreign language alone is actually inadequate. Certainly, there certainly are numerous strings attached to this benefit. The legal actions are frequently mixed up and also misunderstood by someone who has never heard of it or even recognizes it in a different language. Having said that, this interaction void, which has actually existed for many years, may currently be tightened along with the introduction of numerous methods to automate the discovery of authorized motions. Within this particular study, our team presented an Authorize Foreign Language acknowledgment utilizing United States Authorize Foreign Language. Within this particular analysis, the customer needs to have the capacity to squeeze pictures of the possession in motion utilizing an internet electronic camera, and the device will forecast as well as show the title of the recorded picture. To find the possession motion and collect the history to dark, our team employs the HSV color protocol. The pictures go through a collection of handling actions that include numerous personal computer sight methods, including the conversion to grayscale, dilation, and mask function. Additionally, the area of enthusiasm, which, in our instance, is actually the possession motion, is actually segmented. The functions drawn out are actually the binary pixels of the picture. This study utilizes Convolutional Neural Networks (CNN) to categorize the image. The proposed model has the capacity to acknowledge 10 United States Authorized Motion Alphabets along with higher precision. The proposed version has actually attained an exceptional precision of over 90%.
  • A Robust system for disaster detection and management model
    M. P. Karthikeyan, A. Mani, Indhumathi S, Jothika B, Kongara Deepika
    2023 IEEE International Conference on Research Methodologies in Knowledge Management Artificial Intelligence and Telecommunication Engineering Rmkmate 2023, 2023
    Numerous advancements are produced as a result of the development of embedded computer systems and the science of sensors. In this research, a unique sensing network framework for the disaster gathering and analysis, comprising data on the actual surroundings and prospective surviving' messages, is discussed. A centralized information server and a large number of sensor devices make up the overall structure. The main database server supervises the sensor devices' internal ZigBee system, which is coordinated by them. For the purpose of being able to deliver comprehensive catastrophic event data globally, the server must be linked to the internet. An automated configuration that can travel to catastrophe sites and assess the viability of an individual's involvement was built into the framework.
  • SMART ELECTRIC VEHICLE CHARGING SYSTEM USING RFID
    M. P. Karthikeyan, M. Mukesh, R. Karthikeyan, T. S. Jaiganesh, R. Dilip
    2023 IEEE International Conference on Research Methodologies in Knowledge Management Artificial Intelligence and Telecommunication Engineering Rmkmate 2023, 2023
    Electric vehicles (EVs) have gained popularity in recent years due to their environmental friendliness and low operating costs. However, the inconvenience of traditional EV charging methods has been a major barrier to widespread adoption. In this paper, we propose a smart wireless EV charging system that uses the integration of Internet of Things (IoT) and Radio Frequency Identification (RFID) technologies to improve the convenience and efficiency of EV charging. The system allows for automatic charging without the need for physical contact between the charging pad and the EV, thanks to the use of wireless power transfer technology. The system is also equipped with real-time monitoring and control capabilities, allowing users to check the status of their EVs and charging sessions via a mobile app. Additionally, RFID technology is used to enable secure and seamless authentication of the EV and the user. The proposed system has been simulated and evaluated in terms of its performance and energy efficiency, and the results show promising performance. This paper presents a step towards a smarter and more sustainable transportation system.
  • Scrap Management using E-com Online Machine Learning Iscrap Algorithm
    S.Shahul Hammed, M.P. Karthikeyan, R.Pranesh Raj, C. Preethi, K. Haripriya, A. Kathiravan
    International Conference on Sustainable Computing and Smart Systems Icscss 2023 Proceedings, 2023
    The scrap recycler app is an online application where users can sell the scrap materials that are available in the house. Scrap materials are referred to as waste, unused products like broken items, plastics, waste metals, papers, glass etc. Scrap is defined as a material that has no economic value only the basic materials that are available in that scrap can be recovered and recycled.This application serves as a bridge to sell those waste scraps online. The main motto is to create an application that will be used to sell waste scraps and reduce the scraps that are available in the house and increase the recycling process and develop a sustainable environment. By using this application users can directly post the scrap materials online and vendors can be able to see the available scrap materials to be purchased and it is send to recycling stations. This application helps the vendors to easily make profit and it collects the scraps efficiently from the users, by this transportation costs can be managed. Only verified vendors can buy the scrap from the customers so that customer trust is developed and the vendors can mainly focus on customer satisfaction. This study provides a new perspective on selling those available scraps that are available in houses and small organizations using machine learning. The main objective of creating this algorithm is to reduce the usage of waste and reduce the land pollution. The algorithm is going to encounter challenges in sorting scraps and segregating waste, as well as disposing of waste. The machine learning is also used to detect the scraps so that the app will able to detect the scraps and indicate to the vendors. As a consequence, the algorithm is capable of resolving it. The software application is free and is available on the Android platform. The application is user-friendly with a basic structure and easily able to sell scraps online. This software application is developed using MYSQL, android studio, and kotlin.
  • Smart Ambulance for Traffic Management System
    M P Karthikeyan, Samyugdha R, Mithra K, Kaviya G
    Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems Icesc 2021, 2021
  • IOT Based V-Tank
    A. Sai Nandan, B. Sai Sumanth, R. Lilith Kumar, M. P. Karthikeyan
    Lecture Notes in Networks and Systems, 2021
  • Analysis of social network with ontology and deep sentiment durability detection (SSD) model for green community
    Journal of Green Engineering, 2020
  • Hardware based anti-theft systemfor Smartphones
    International Journal of Recent Technology and Engineering, 2019
  • Survey of retinal image analysis for glaucomatous classification and exudates detection
    M. Karthikeyan, D. Malathi
    2013 International Conference on Information Communication and Embedded Systems Icices 2013, 2013

RECENT SCHOLAR PUBLICATIONS

  • Automated Detection Model (ADM) For Glaucoma, Exudate and Diabetic Retinopathy (DR) Diagnosis Using Fundus Images
    MP Karthikeyan, EAM Anita, DM Geetha
    2025 2nd International Conference on Research Methodologies in Knowledge … , 2025
    2025
  • Exploring the Various Machine Learning Models for Image Generation-A Comprehensive Survey Unlocking the Future of Digital Creativity
    M Balasubramanian, M Naveen Joel, MP Karthikeyan
    International Conference on Advances in Artificial Intelligence and Machine … , 2024
    2024
    Citations: 1
  • Control of Autonomous Underwater Vehicles
    MP Karthikeyan, S Anitha Jebamani, P Umaeswari, K Chitti Babu, ...
    Artificial Intelligence for Autonomous Vehicles, 209-227 , 2024
    2024
    Citations: 3
  • A Robust system for disaster detection and management model
    MP Karthikeyan, A Mani, K Deepika
    2023 International Conference on Research Methodologies in Knowledge … , 2023
    2023
  • Smart Electric Vehicle Charging System Using RFID
    MP Karthikeyan, M Mukesh, R Karthikeyan, TS Jaiganesh, R Dilip
    2023 International Conference on Research Methodologies in Knowledge … , 2023
    2023
    Citations: 3
  • Towards developing an automated technique for glaucomatous image classification and diagnosis (AT‑GICD) using neural networks
    DMG M. P. Karthikeyan, E. A. Mary Anita
    International Journal of Information Technology , 2023
    2023
    Citations: 8
  • A review on phytochemistry and pharmacological activities of Schleichera oleosa (Lour.) Oken
    M Karthikeyan, SK Raju, R Karthikeyan, S Arivanantham, S Kumar, ...
    World J Adv Res Rev 17, 1101-7 , 2023
    2023
    Citations: 6
  • Text classification; language-independent tokenization; sub word tokenization.
    MP Karthikeyan, EA Mary Anita
    Intelligent Automation & Soft Computing 35 (1) , 2023
    2023
    Citations: 2
  • IM-EDRD from Retinal Fundus Images Using Multi-Level Classification Techniques
    MP Karthikeyan, EA Anita
    INTELLIGENT AUTOMATION AND SOFT COMPUTING 35 (1), 567-580 , 2023
    2023
    Citations: 2
  • Smart ambulance for traffic management system
    MP Karthikeyan, R Samyugdha, K Mithra, G Kaviya
    2021 Second International Conference on Electronics and Sustainable … , 2021
    2021
    Citations: 5
  • IOT Based V-Tank
    A Sai Nandan, B Sai Sumanth, R Lilith Kumar, MP Karthikeyan
    Next Generation of Internet of Things: Proceedings of ICNGIoT 2021, 513-518 , 2021
    2021
  • Fall Detection Using Computer Vision And Machine Learning.
    K M. P., V S., SK C. R., S R.
    Turkish Online Journal of Qualitative Inquiry 12 (4), 2192-2199 , 2021
    2021
  • Protected Banking Verification By Figure Pixel Comparison And Bitcoin Transaction Using Blockchain
    TCJJ M.P.Karthikeyan, C. Balakrishnan, Karthik Elangovan
    Turkish Journal of Computer and Mathematics Education 12 (6), 316-320 , 2021
    2021
  • Analysis of Social Network with Ontology and Deep Sentiment Durability Detection (SSD) Model for Green Community
    MP Karthikeyan
    Journal of Green Engineering (JGE) 10 (Issue-6), 2661–2677. , 2020
    2020
    Citations: 2
  • Nutritional and functional variablitity of Nutri cereals
    P Karuppasamy, D Malathi, M Karthikeyan
    Int J Chem Stud 8, 125-129 , 2020
    2020
    Citations: 2
  • 5G Network Design for Water Quality Monitoring using Agricultural IoT
    T. C. Jerlin Jenita, Dr. Saraswathi V, A. V. Kalpana, M. P. Karthikeyan
    Test Engineering & Management 82, 8827-8834 , 2020
    2020
  • Data Hiding in HDR Images
    MP Karthikeyan
    International Journal of Advance Engineering and Research Development 5 (2), 378 , 2018
    2018
  • Authentication through identification of Glaucoma, Exudates and Diabetes using Retinal Scan and Wavelet Filters
    MP Karthikeyan
    National Conference on Recent Innovations in Software Engineering and … , 2017
    2017
  • A Survey on Identification of Glaucoma, Exudates using Retinal Scan and Wavelet Filters
    R Saranya, MT Selvi, GU Maheshwari, MP Karthikeyan
    International Journal of Engineering Research 6 (3), 132-135 , 2017
    2017
  • A Survey on Effective Attendance Marking Using Face Recognition Behavior Monitoring and RFID
    K M.P
    International Journal of Engineering Research 6 (3), 136-139 , 2017
    2017
    Citations: 2

MOST CITED SCHOLAR PUBLICATIONS

  • Towards developing an automated technique for glaucomatous image classification and diagnosis (AT‑GICD) using neural networks
    DMG M. P. Karthikeyan, E. A. Mary Anita
    International Journal of Information Technology , 2023
    2023
    Citations: 8
  • A review on phytochemistry and pharmacological activities of Schleichera oleosa (Lour.) Oken
    M Karthikeyan, SK Raju, R Karthikeyan, S Arivanantham, S Kumar, ...
    World J Adv Res Rev 17, 1101-7 , 2023
    2023
    Citations: 6
  • Smart ambulance for traffic management system
    MP Karthikeyan, R Samyugdha, K Mithra, G Kaviya
    2021 Second International Conference on Electronics and Sustainable … , 2021
    2021
    Citations: 5
  • Control of Autonomous Underwater Vehicles
    MP Karthikeyan, S Anitha Jebamani, P Umaeswari, K Chitti Babu, ...
    Artificial Intelligence for Autonomous Vehicles, 209-227 , 2024
    2024
    Citations: 3
  • Smart Electric Vehicle Charging System Using RFID
    MP Karthikeyan, M Mukesh, R Karthikeyan, TS Jaiganesh, R Dilip
    2023 International Conference on Research Methodologies in Knowledge … , 2023
    2023
    Citations: 3
  • Text classification; language-independent tokenization; sub word tokenization.
    MP Karthikeyan, EA Mary Anita
    Intelligent Automation & Soft Computing 35 (1) , 2023
    2023
    Citations: 2
  • IM-EDRD from Retinal Fundus Images Using Multi-Level Classification Techniques
    MP Karthikeyan, EA Anita
    INTELLIGENT AUTOMATION AND SOFT COMPUTING 35 (1), 567-580 , 2023
    2023
    Citations: 2
  • Analysis of Social Network with Ontology and Deep Sentiment Durability Detection (SSD) Model for Green Community
    MP Karthikeyan
    Journal of Green Engineering (JGE) 10 (Issue-6), 2661–2677. , 2020
    2020
    Citations: 2
  • Nutritional and functional variablitity of Nutri cereals
    P Karuppasamy, D Malathi, M Karthikeyan
    Int J Chem Stud 8, 125-129 , 2020
    2020
    Citations: 2
  • A Survey on Effective Attendance Marking Using Face Recognition Behavior Monitoring and RFID
    K M.P
    International Journal of Engineering Research 6 (3), 136-139 , 2017
    2017
    Citations: 2
  • Exploring the Various Machine Learning Models for Image Generation-A Comprehensive Survey Unlocking the Future of Digital Creativity
    M Balasubramanian, M Naveen Joel, MP Karthikeyan
    International Conference on Advances in Artificial Intelligence and Machine … , 2024
    2024
    Citations: 1
  • Automated Detection Model (ADM) For Glaucoma, Exudate and Diabetic Retinopathy (DR) Diagnosis Using Fundus Images
    MP Karthikeyan, EAM Anita, DM Geetha
    2025 2nd International Conference on Research Methodologies in Knowledge … , 2025
    2025
  • A Robust system for disaster detection and management model
    MP Karthikeyan, A Mani, K Deepika
    2023 International Conference on Research Methodologies in Knowledge … , 2023
    2023
  • IOT Based V-Tank
    A Sai Nandan, B Sai Sumanth, R Lilith Kumar, MP Karthikeyan
    Next Generation of Internet of Things: Proceedings of ICNGIoT 2021, 513-518 , 2021
    2021
  • Fall Detection Using Computer Vision And Machine Learning.
    K M. P., V S., SK C. R., S R.
    Turkish Online Journal of Qualitative Inquiry 12 (4), 2192-2199 , 2021
    2021
  • Protected Banking Verification By Figure Pixel Comparison And Bitcoin Transaction Using Blockchain
    TCJJ M.P.Karthikeyan, C. Balakrishnan, Karthik Elangovan
    Turkish Journal of Computer and Mathematics Education 12 (6), 316-320 , 2021
    2021
  • 5G Network Design for Water Quality Monitoring using Agricultural IoT
    T. C. Jerlin Jenita, Dr. Saraswathi V, A. V. Kalpana, M. P. Karthikeyan
    Test Engineering & Management 82, 8827-8834 , 2020
    2020
  • Data Hiding in HDR Images
    MP Karthikeyan
    International Journal of Advance Engineering and Research Development 5 (2), 378 , 2018
    2018
  • Authentication through identification of Glaucoma, Exudates and Diabetes using Retinal Scan and Wavelet Filters
    MP Karthikeyan
    National Conference on Recent Innovations in Software Engineering and … , 2017
    2017
  • A Survey on Identification of Glaucoma, Exudates using Retinal Scan and Wavelet Filters
    R Saranya, MT Selvi, GU Maheshwari, MP Karthikeyan
    International Journal of Engineering Research 6 (3), 132-135 , 2017
    2017