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Mr. Kabilan S
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Academic Career Length
2Years (2025-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
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Conference Paper
SRSANMUGASUNDARAM RAVICHANDRAN
SANMUGASUNDARAM RAVICHANDRANHSHui-Kai Su
Hui-Kai SuWKWen-Kai Kuo
Wen-Kai KuoMMManikandan Mahalingam
Manikandan MahalingamKJKanimozhi Janarthanan
Kanimozhi JanarthananBSBruhathi Sathyanarayanan
Bruhathi Sathyanarayanan +1
Advancements in image processing have advanced medical diagnostics, especially in image classification, impacting healthcare by offering faster and more accurate analyses of magnetic resonance imaging (MRI) and X-rays. The manual examination of these images is slow, error-prone, and costly. Therefore, we propose a new method focusing on the Pap smear exam for early cervical cancer detection. Using a convolutional neural network (CNN) and the SIPaKMeD dataset, cervical cells are classified into normal, precancerous, and benign cells after segmentation. The CNN’s architecture is simple yet efficient, achieving a 91.29% accuracy.
Conference Paper
SRSANMUGASUNDARAM RAVICHANDRAN
SANMUGASUNDARAM RAVICHANDRANHSHui-Kai Su
Hui-Kai SuWKWen-Kai Kuo
Wen-Kai KuoMMManikandan Mahalingam
Manikandan MahalingamKJKanimozhi Janarthanan
Kanimozhi JanarthananKSKabilan S
Kabilan S +1
We implemented a robust framework for diabetes prediction, leveraging a diverse array of machine learning algorithms. Through an analysis of diabetes-related characteristics, we identified the most accurate classifier. Diverse algorithms were tested to compare their accuracies with the complexities of data: K-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), logistic regression (LR), Naïve Bayes (NB), and decision tree (DT). The decision tree algorithm demonstrated the best accuracy in predicting diabetes.
About Me
Kabilan S was born in 2003 and hails from Chennai, Tamil Nadu, India. He earned his Bachelor of Engineering degree in Electronics and Communication Engineering from Rajalakshmi Institute of Technology. Passionate about innovation and technology, Kabilan has developed a strong foundation in the field of electronics, with focused interests in the areas of IoT, Medical IoT, and Agriculture IoT.
Kabilan is currently working as a Hardware Engineer at a startup company, where he actively contributes to the design and development of cutting-edge embedded systems and IoT-based solutions. His academic and practical experiences are enriched by a notable internship at the Indian Institute of Technology (IIT) Roorkee, where he contributed to research and development initiatives.
Throughout his journey, he has been involved in several impactful projects, including a smart aquaponics system and a smart IV drip monitoring system, among many other innovative IoT applications aimed at solving real-world challenges.
With a deep commitment to learning and innovation, Kabilan continues to explore new possibilities in the field of electronics and embedded systems, striving to create meaningful contributions to the world of technology.