S.Yuvaraj

@sece.ac.in

Assistant Professor and Computer Science and Engineering
Sri Eshwar College of Engineering

S.Yuvaraj


               Download Compact PDF  
https://researchid.co/yuvaraj.s

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Artificial Intelligence, Software, Human-Computer Interaction
8

Scopus Publications

66

Scholar Citations

5

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • An Overview of Different Types of Recommendations Systems-A Survey
    Premkumar Duraisamy, S. Yuvaraj, Yuvaraj Natarajan, V. Niranjani
    2023 International Conference on Innovative Trends in Information Technology Icitiit 2023, 2023
    In recent years the boom of internet and social media usage everyone spend their invaluable time in social media app and looking for the solution for all kind of their problems. This work analysis deeply on how recommendation system works and its types in different platforms. Most of the modern recommendation system use machine learning algorithms like linear regression, random forest regression and support vector model with collaborative filtering method. Recommendation is nothing but an choice making system. It is vary from person to person based on their interest, culture, locality, education background, interpersonal skills etc., The huge item can be filtered from one by one based on each parameter and finally it will reach the right recommendation item. The research community has worked tremendous way in the field of recommendation system and produced huge variety of result. This survey enlightening the ideas about variety of recommendation system and techniques used by the research community.
  • A Survey on Human Face Emotion Recognition using Machine Learning Models
    S. Yuvaraj, J. Vijay Franklin, V. S. Prakash, A. Anandaraj, R. Subha
    2023 9th International Conference on Advanced Computing and Communication Systems Icaccs 2023, 2023
    Human Face Emotion Recognition (HFER) is a field that studies the human state of mind through different facial expressions. In this paper, the comparative study is made on four different machine learning methods such as CNN, Bidirectional Convolutional LSTM, Multiple Pipelines, and Transfer Learning algorithms based on the various universal human emotions like Happy, Sad, Surprise, Fear, Anger, Disgust, Neutral and Contempt. Two Image data sets that carry static images with a different set of emotions are used in the methods and the accuracy level of each method is compared and analysed along with other metrics such as Precision, Recall, and F1 Scores are also considered.
  • An Adaptive Deep Belief Feature Learning Model for Cognitive Emotion Recognition
    S. Yuvaraj, J.Vijay Franklin, V.S. Prakash, A. Anandaraj
    8th International Conference on Advanced Computing and Communication Systems Icaccs 2022, 2022
    Cognitive emotion recognition using facial expression is the sub-field of social signal processing. It is broadly utilized in various fields, specifically human interaction and computer vision. Different investigators use learning approaches to construct an efficient system for automatic emotion recognition. However, predicting certain emotions like surprise, fear, sadness, happiness, disgust, and anger is still challenging in computer vision. However, deep learning has attained the interest of various researchers to resolve real-time problems like emotion recognition. This work concentrates on modelling and efficient Deep Belief Feature Learning (DBFL) for emotion recognition. The model uses a deep network layer to predict the feature information and further classification performance. The model gives 98% average prediction accuracy compared to various other approaches. The evaluation of the model is conducted over the public dataset, and the classification outcomes attained by the model demonstrates the significance of the proposed DBFL.
  • Sentiment Analysis using Machine learning algorithm using speech signal
    R. Deepa, S. Yuvaraj, T. Preethi, Pradnya Patil, Ilayaraja N
    2nd IEEE International Conference on Advanced Technologies in Intelligent Control Environment Computing and Communication Engineering Icatiece 2022, 2022
    With the growth of online social networks, people now have a new forum for sharing their thoughts and perspectives with family, friends, and other users on various issues and topics. Users can express their thoughts and emotions in various forms like images, text, memes, postings, and audio/video messages, among which text is the most popular way to communicate on social media. In this study, we collected, tested, and analyzed the data from the most popular social media, Twitter. The primary goal of this work is to identify and assess the emotions and thoughts expressed by users in their text-based Twitter tweets. The Bag-Of-Words model, while the most popular technique for sentiment analysis, has two critical disadvantages, such as applying a manual lexicon for establishing word analysis. The second drawback is it analyses sentiments with high error because it refuses to acknowledge the language grammar impacts of the words and ignores semantics. In this research, we provide a unique approach for assessing online sentiments in a single domain and a solution for addressing crucial challenges in sentiment analysis that improves sentiment analysis accuracy. Using the improved bag-of-words model, word weight is taken to determine the polarity and score instead of term frequency. The proposed method automatically categorizes the keywords and characteristics related to scientific subject areas. This work provides an effective solution for typical sentiment analysis issues. The proposed model is enhanced to achieve maximum sentiment analysis precision.
  • Improved Privacy Conservation Applicability for the Disturbed Data in Multi Partitioned Data Collection Environment
    V.S. Prakash, K. Chitra, Britto Jacob S, S. Yuvaraj, Shiva Kumar B. N
    Proceedings of the 2022 3rd International Conference on Communication Computing and Industry 4 0 C2i4 2022, 2022
    The perturbation technique was widely considered for the protection of the privacy for different datasets in data mining. Multi-partitioned datasets generally consist of together horizontal and vertical data Collection, that are a existing demand in the data mining environment of e- Pay and e-Commerce. In the phase of perturbation, arbitrary disturbance from a known scattering is processed as data susceptible to privacy, prior to the information miner being thrown. Consequently, the data-miner reconstitutes estimates for the specific distribution of data from the disrupted data and exercises the restored delivery of data mining principles. According to the count of noise, information loss versus privacy protection in perturbation-based techniques is a constant transaction. The problem is to what degree of privacy are consumers able to cooperate? This is a choice which is shifting from person to person. The first work is to define the technique of data perturbation with validation and authentication in order to determine a trade-off between data protection and the usability of the data. Diverse people may have different secrecy strategies, focused on customs and cultures. Inappropriately, the earlier privacy-included perturbation that preserves data mining procedures does not allow entities to choose their preferred levels of privacy. It is a negative thing, because privacy is a preference for individuals. Researchers in this study suggest an independently adaptable perturbation model that allows persons to select their own degree of confidentiality. The success of the proposed model lies in Enhancing the Privacy Conservation Applicability for Disturbed Data in Multi-partitioned datasets (PADDM), as validated by numerous studies performed on both unreal and real-world data Collection. Focused on the experimental evaluation, researchers are proposing a simple, useful and resourceful method for building data mining representations from disturbed facts and enhancing the privacy conservation process.
  • An integrated cognitive system (ICS) for diabetes mellitus
    International Journal of Scientific and Technology Research, 2019
  • Automatic Detection of Lung Cancer Identification using ENNPSO Classification
    B. Hemalatha, S. Yuvaraj, K. V. Kiruthikaa, V. Viswanathan
    Proceedings of the 2019 International Conference on Advances in Computing and Communication Engineering Icacce 2019, 2019
    The main source of lung cancer is to gasping the tobacco smoke regularly, which affects around 90% of lung cancers. Cancer cells are to be carried to and from the lungs within the blood or lymph fluid ambience the lung tissue. Early diagnosis and treatment can save life. In this, the image processing techniques have been utilized to identify the lung cancer. Initially, the CT scan image is pre-processed for removing the unwanted signals and smoothing them by employing Improved Kaun Filter (IKF). Subsequently, the preprocessed image is portioned by an Active contour method to get exactness of segmented results. Next, specific features are extracted to raise the anticipated accuracy. At last, the tumour has been categorized by Elman Neural Network (ENN) and weights are optimized with PSO and compared the accuracy results with SVM, RBFN and ANFIS.
  • Analysis of prediction accuracy of heart diseases using supervised machine learning techniques for developing clinical decision support systems
    International Journal of Recent Technology and Engineering, 2019

RECENT SCHOLAR PUBLICATIONS

  • PLANTS IN SPACE: GROWING VEGETABLES IN SPACE-A REVIEW
    SN Darshan, C Suneetha, S Yuvaraj, K PN, S TR, MS TS
    Plant Archives 26 (1), 445-449 , 2026
    2026
  • OPTIMIZATIONOF SEASON AND GROWING CONDITIONS FOR MAXIMIZING SUCCESS OF TAMARIND SOFTWOOD
    R Praveenakumar, C Suneetha, S Yuvaraj, P Krishnamma, TR Sunitha, ...
    Plant Archives (09725210) 25 (1) , 2025
    2025
  • Screening of Muskmelon Genotypes (Cucumis melo L.) for Drought Tolerance
    S Kavya, C Suneetha, M Shivapriya, P Bhavani, TR Sunitha, ...
    Indian Journal of Ecology 52 (6), 1477-1482 , 2025
    2025
  • Molecular Diversity of Fern Species of Agumbe Ghats of Karnataka using ISSR Markers
    C Suneetha, N Nagesha, S Yuvaraj, A Nataraja, K Kandpal, V Muttu, ...
    Indian Journal of Ecology 52 (5), 935-939 , 2025
    2025
  • The Adverse Medication Interaction and Disease Correlation Analysis Using Deep Learning
    R Subha, S Yuvaraj, BS Santhosh, S Raghul, A Karthikeyan, ...
    2024 International Conference on Computing and Intelligent Reality … , 2024
    2024
    Citations: 1
  • Enhancing Consumer Sentiment Analysis and Product Improvement with Aspect-Optimized Adaptive GCN (AOA-GCN)
    S Annamalai, TN Priya, N Basker, S Yuvaraj, S Ramasami, D Suresh
    2024 International Conference on Integrated Intelligence and Communication … , 2024
    2024
    Citations: 1
  • Enhancing Aspect-Based Sentiment Analysis Through Multi-Granularity Information Sharing
    N Ilayaraja, S Yuvaraj, C Pratibha, E Glory
    2024 International Conference on Data Science and Network Security (ICDSNS), 1-7 , 2024
    2024
  • Boundary Feature-Based Leaf Disease Detection Using Differential Network
    A Mitra, P Ponnila, S Yuvaraj, R Chowdhury, P Kumar, K Sangamithrai
    2024 International Conference on Data Science and Network Security (ICDSNS), 1-6 , 2024
    2024
    Citations: 3
  • Advances and Challenges in Color and Multispectral Image Retrospective Analysis
    I Soni, S Yuvaraj, A Kaur, B Jayaprakash, VK Kolekar, K Yuvaraj
    2024 15th International Conference on Computing Communication and Networking … , 2024
    2024
  • The Impact of Rising Temperatures and Weather Patterns on Grassland Fire Risk: A Machine Learning Approach
    S Yuvaraj, R Subha, A Karthikeyan, BS Santhosh, S Raghul, ...
    2024 International Conference on Science Technology Engineering and … , 2024
    2024
  • Energy-Synchronized Operation Frequency Management Technique for Internet of Things (IoT)-based Health Monitoring Systems
    T Gowri, R Mithra, CS Nageswari, S Yuvaraj, J Sathiyamurthi
    2024 Ninth International Conference on Science Technology Engineering and … , 2024
    2024
  • A study on machine learning models for segmentation and classification of skin diseases
    D Vishal, MV Manikandaprabhu, B Vishnuvardhan, S Yuvaraj
    AIP Conference Proceedings 3035 (1), 020012 , 2024
    2024
    Citations: 3
  • Identification of Autism Spectrum Disorder (ASD) in adults through various machine learning algorithms
    S Yuvaraj, S Sugavanaesh, CT Kumar, G Saran, R Subha
    2024 2nd International Conference on Intelligent Data Communication … , 2024
    2024
    Citations: 5
  • A model for segmentation and classification of skin diseases using yolo algorithm
    D Vishal, B Vishnuvardhan, S Yuvaraj
    2023 Fourth International Conference on Smart Technologies in Computing … , 2023
    2023
    Citations: 2
  • A dense layer model for cognitive emotion recognition with feature representation
    S Yuvaraj, J Vijay Franklin
    Journal of Intelligent & Fuzzy Systems 45 (5), 8989-9005 , 2023
    2023
    Citations: 2
  • A Survey on Human Face Emotion Recognition using Machine Learning Models
    S Yuvaraj, JV Franklin, VS Prakash, A Anandaraj, R Subha
    2023 9th International Conference on Advanced Computing and Communication … , 2023
    2023
    Citations: 3
  • An overview of different types of recommendations systems-a survey
    P Duraisamy, S Yuvaraj, Y Natarajan, V Niranjani
    2023 4th International Conference on Innovative Trends in Information … , 2023
    2023
    Citations: 15
  • Sentiment Analysis using Machine learning algorithm using speech signal
    R Deepa, S Yuvaraj, T Preethi, P Patil
    2022 Second International Conference on Advanced Technologies in Intelligent … , 2022
    2022
    Citations: 2
  • Improved Privacy Conservation Applicability for the Disturbed Data in Multi Partitioned Data Collection Environment
    VS Prakash, K Chitra, S Yuvaraj
    2022 3rd International Conference on Communication, Computing and Industry 4 … , 2022
    2022
    Citations: 2
  • Epilepsy detection method based on magnitude squared coherence and machine learning
    M Janani, S Rathna, S Yuvaraj, S Karthik, S Mohan
    2022 IEEE North Karnataka Subsection Flagship International Conference … , 2022
    2022

MOST CITED SCHOLAR PUBLICATIONS

  • An overview of different types of recommendations systems-a survey
    P Duraisamy, S Yuvaraj, Y Natarajan, V Niranjani
    2023 4th International Conference on Innovative Trends in Information … , 2023
    2023
    Citations: 15
  • An adaptive deep belief feature learning model for cognitive emotion recognition
    S Yuvaraj, JV Franklin, VS Prakash, A Anandaraj
    2022 8th International Conference on Advanced Computing and Communication … , 2022
    2022
    Citations: 7
  • Analysis of prediction accuracy of heart diseases using supervised machine learning techniques for developing clinical decision support systems
    KV Kiruthikaa, J VF, S Yuvaraj
    International Journal of Recent Technology and Engineering 7 (45), 433-437 , 2018
    2018
    Citations: 6
  • Identification of Autism Spectrum Disorder (ASD) in adults through various machine learning algorithms
    S Yuvaraj, S Sugavanaesh, CT Kumar, G Saran, R Subha
    2024 2nd International Conference on Intelligent Data Communication … , 2024
    2024
    Citations: 5
  • Automatic detection of lung cancer identification using ENNPSO classification
    B Hemalatha, S Yuvaraj, KV Kiruthikaa, V Viswanathan
    2019 International Conference on Advances in Computing and Communication … , 2019
    2019
    Citations: 5
  • A novel hybrid optimization algorithm for data clustering
    S Yuvaraj, M Krishnamoorthi
    International Journal of Computer Applications 212, 39-43 , 2013
    2013
    Citations: 5
  • A Study On Cognitive Computing Methodologies For Intelligent Decision Making And Problem Solving
    KT Yuvaraj.S, Vijay Franklin.J,Kiruthikaa.K.V,Ramya R
    International Journal of Scientific and Technology Research 9 (6), 602-606 , 2020
    2020
    Citations: 4
  • Boundary Feature-Based Leaf Disease Detection Using Differential Network
    A Mitra, P Ponnila, S Yuvaraj, R Chowdhury, P Kumar, K Sangamithrai
    2024 International Conference on Data Science and Network Security (ICDSNS), 1-6 , 2024
    2024
    Citations: 3
  • A study on machine learning models for segmentation and classification of skin diseases
    D Vishal, MV Manikandaprabhu, B Vishnuvardhan, S Yuvaraj
    AIP Conference Proceedings 3035 (1), 020012 , 2024
    2024
    Citations: 3
  • A Survey on Human Face Emotion Recognition using Machine Learning Models
    S Yuvaraj, JV Franklin, VS Prakash, A Anandaraj, R Subha
    2023 9th International Conference on Advanced Computing and Communication … , 2023
    2023
    Citations: 3
  • A model for segmentation and classification of skin diseases using yolo algorithm
    D Vishal, B Vishnuvardhan, S Yuvaraj
    2023 Fourth International Conference on Smart Technologies in Computing … , 2023
    2023
    Citations: 2
  • A dense layer model for cognitive emotion recognition with feature representation
    S Yuvaraj, J Vijay Franklin
    Journal of Intelligent & Fuzzy Systems 45 (5), 8989-9005 , 2023
    2023
    Citations: 2
  • Sentiment Analysis using Machine learning algorithm using speech signal
    R Deepa, S Yuvaraj, T Preethi, P Patil
    2022 Second International Conference on Advanced Technologies in Intelligent … , 2022
    2022
    Citations: 2
  • Improved Privacy Conservation Applicability for the Disturbed Data in Multi Partitioned Data Collection Environment
    VS Prakash, K Chitra, S Yuvaraj
    2022 3rd International Conference on Communication, Computing and Industry 4 … , 2022
    2022
    Citations: 2
  • The Adverse Medication Interaction and Disease Correlation Analysis Using Deep Learning
    R Subha, S Yuvaraj, BS Santhosh, S Raghul, A Karthikeyan, ...
    2024 International Conference on Computing and Intelligent Reality … , 2024
    2024
    Citations: 1
  • Enhancing Consumer Sentiment Analysis and Product Improvement with Aspect-Optimized Adaptive GCN (AOA-GCN)
    S Annamalai, TN Priya, N Basker, S Yuvaraj, S Ramasami, D Suresh
    2024 International Conference on Integrated Intelligence and Communication … , 2024
    2024
    Citations: 1
  • PLANTS IN SPACE: GROWING VEGETABLES IN SPACE-A REVIEW
    SN Darshan, C Suneetha, S Yuvaraj, K PN, S TR, MS TS
    Plant Archives 26 (1), 445-449 , 2026
    2026
  • OPTIMIZATIONOF SEASON AND GROWING CONDITIONS FOR MAXIMIZING SUCCESS OF TAMARIND SOFTWOOD
    R Praveenakumar, C Suneetha, S Yuvaraj, P Krishnamma, TR Sunitha, ...
    Plant Archives (09725210) 25 (1) , 2025
    2025
  • Screening of Muskmelon Genotypes (Cucumis melo L.) for Drought Tolerance
    S Kavya, C Suneetha, M Shivapriya, P Bhavani, TR Sunitha, ...
    Indian Journal of Ecology 52 (6), 1477-1482 , 2025
    2025
  • Molecular Diversity of Fern Species of Agumbe Ghats of Karnataka using ISSR Markers
    C Suneetha, N Nagesha, S Yuvaraj, A Nataraja, K Kandpal, V Muttu, ...
    Indian Journal of Ecology 52 (5), 935-939 , 2025
    2025