Beulah A

@rajalakshmi.org

Associate Professor at Department of Artificial Intelligence and Data Science
Rajalakshmi Engineering College

Beulah A


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https://researchid.co/beulaha

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Science Applications
20

Scopus Publications

102

Scholar Citations

6

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Lumbar Spinal Stenosis Detection from Sagittal and Axial MR Images using Hybrid of Deep Kronecker Network and SpinalNet
    A. Beulah
    European Spine Journal, 2025
  • ImageCLEF-Medical 2025: MedCLIP Model for Medical Caption Prediction and Concept Detection
    Ceur Workshop Proceedings, 2025
  • REC_Cryptix at JOKER CLEF 2025: Teaching Machines to Laugh: Multilingual Humor Detection and Translation
    Ceur Workshop Proceedings, 2025
  • RECAIDSTechTitans at CLEF 2025: Simplifying Scientific Text and Identifying Spurious Sentences using T5
    Ceur Workshop Proceedings, 2025
  • Cell classification in microscopic images for anemia detection
    Priyadharsini RAVISANKAR, Beulah ARUL, Srivarsha ELANGO
    Revista Romana De Informatica Si Automatica, 2024
    Sickle cell anemia is an inherited disorder of the red blood cells in which there is an insufficient number of healthy red blood cells to transport oxygen effectively throughout the body. When observed under a microscope, the blood cells of an individual with sickle cell anemia exhibit a crescent or sickle-like shape. Image segmentation and classification techniques are necessary for detecting sickle cell anemia from microscopic images. Segmentation of the images is performed to distinguish between healthy and sickle (unhealthy) red blood cells. A mask of the microscopic image is first generated, which aids in the classification of cells. The mask generated is then further classified into circular, elongated and other cells, with the help of image processing. The erythrocytesIDB dataset is used for the detection of cells, which was provided by Universitat de les Illes Balears and available at http://erythrocytesidb.uib.es/. Upon the successful classification of cells into their respective types, it is concluded that circular cells are representative of healthy red blood cells, whereas elongated cells are characteristic of sickle cells. However, cells classified as "others" are indeterminate, and their association with sickle cells is uncertain, hence presenting a degree of ambiguity. In terms of performance evaluation, the proposed method achieved an accuracy of 94.907% in cell classification.
  • AirStrum: A virtual guitar using real-time hand gesture recognition and strumming technique
    Beulah ARUL, Shashank PANDA, Tushar NAIR
    Revista Romana De Informatica Si Automatica, 2024
    The efforts in the field of virtualizing the guitar into well-modelled software systems have faced a lot of practical limitations. The existing guitar simulation programs require additional devices such as Electromyography (EMG) controllers, or Musical Instrument Digital Interface (MIDI)-based recording devices. The EMG-based device is still a work in progress, the device is expensive and it was not very well received by the instrumentalists. There exists a gap in the bridge that joins physical instruments to their software counterparts. In this context, this paper aims to significantly remove the inaccuracies and drawbacks related to the existing solutions by accounting for the individual roles that each hand plays in the act of guitar strumming and consolidating them into a single system. The design of the proposed AirStrum system involves a multi-step process. Initially, a dataset is created by recording images of hand gestures corresponding to the playing of various chords on a guitar. The palm is detected, and its related skeleton image is generated using MediaPipe. Subsequently, a model based on a Convolutional Neural Network (CNN) is trained and validated using the employed dataset to adeptly recognize and classify guitar chords. Additionally, this model incorporates a velocity detection function for the strumming hand. Finally, the proposed system can play different sounds by inferring both the played chord and the strumming velocity from human actions. This comprehensive approach enables a sophisticated virtual guitar experience based on a system that responds dynamically to the users' gestures and strumming techniques. The conducted experiments demonstrate that AirStrum achieves an accuracy of 95.92%, and a brief preliminary survey related to its perceived utility and usability received a positive feedback rate of 58% from eight guitar players.
  • Diagnosis of Central Canal Spinal Stenosis from Lumbar Mid-sagittal MR Images
    A Beulah, T. Sree Sharmila, V. K. Pramod
    Proceedings 3rd International Conference on Advances in Computing Communication and Applied Informatics Accai 2024, 2024
    Central canal spinal stenosis is a significant ailment that impacts the spinal cord of humans. The current automated diagnostic methods for spinal stenosis are unable to diagnose minor abnormalities that may be present in the spinal cord. This paper introduces a novel approach for diagnosing central canal spinal stenosis from T2-weighted lumbar Magnetic Resonance (MR) images captured in the sagittal plane. A segmentation algorithm based on morphology is implemented for segmenting the spinal cord. After segmenting the image, the spinal cord’s skeleton is extracted, and overlapping sub-images are generated. The hybrid of statistical texture features and a novel Spinal Cord Projection Descriptor (SCPD) are extracted for all subimages. Using these features, a k-Nearest Neighbors (k-NN) classifier is trained and a model is constructed. Upon receiving a new test image, the system undergoes these processes to generate features. The features are then utilized by the model to classify the sub-image as either stenosis or non-stenosis. To evaluate the effectiveness of the model, a k-fold validation technique is employed. The constructed model has demonstrated an improved performance in accurately identifying the stenosis region and non-stenosis region, achieving an accuracy rate of 95.19%. The experiments conducted illustrate that the proposed stenosis diagnostic system outperforms existing methods in terms of its effectiveness and accuracy. This study provides promising results for the development of an effective automated diagnostic system for central canal stenosis, which could be of significant benefit to medical professionals and patients. Further research could focus on validating the proposed approach on larger datasets and integrating it into clinical practice.
  • Java code obfuscator to prevent reverse engineering of android application
    Harshavardhan Parandaman, Beulah Arul, Logesh Dinakaran
    Aip Conference Proceedings, 2023
  • Preface
    IFIP Advances in Information and Communication Technology, 2023
  • Degenerative disc disease diagnosis from lumbar MR images using hybrid features
    A. Beulah, T. Sree Sharmila, V. K. Pramod
    Visual Computer, 2022
  • Optimized Image Edge Detection Approach using Fractional Order Calculus
    Srinithyee S K, Srivarsha E, R. Priyadharsini, A. Beulah
    Proceedings of the 6th International Conference on Communication and Electronics Systems Icces 2021, 2021
  • Detection of Electronic Devices in real images using Deep Learning Techniques
    Krijeshan G, Raghul P, Nachiappan N N, A. Beulah, R. Priyadharshini
    2021 5th International Conference on Computer Communication and Signal Processing Icccsp 2021, 2021
  • Home Security System for the Hearing Impaired
    Talapala Sneha, Ssneha Balasubramanian, Vaishali R, Jay Vishaal J, Beulah A, S Angel Deborah
    2021 5th International Conference on Computer Communication and Signal Processing Icccsp 2021, 2021
  • Identification of sickle cells in erythrocytes images using shape descriptors
    L. Yamini, R. Priyadharsini, A. Beulah
    Advances in Parallel Computing, 2021
  • Spinal Cord Segmentation in Lumbar MR Images
    A. Beulah, T. Sree Sharmila, T. Kanmani
    Lecture Notes on Data Engineering and Communications Technologies, 2020
  • Disc bulge diagnostic model in axial lumbar MR images using Intervertebral disc Descriptor (IdD)
    A. Beulah, T. Sree Sharmila, V. K. Pramod
    Multimedia Tools and Applications, 2018
  • Optic disc and cup segmentation in fundus retinal images using feature detection and morphological techniques
    R. Priyadharsini, A. Beulah, T. Sree Sharmila Anon
    Current Science, 2018
  • EM algorithm based intervertebral disc segmentation on MR images
    A. Beulah, T. Sree Sharmila
    International Conference on Computer Communication and Signal Processing Special Focus on Iot Icccsp 2017, 2017
  • Classification of Intervertebral Disc on Lumbar MR Images using SVM
    Beulah A., T. Sree Sharmila
    Proceedings of the 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology Icatcct 2016, 2017
  • Human spine structure localization on MRI - a survey
    A. Beulah
    Indian Journal of Science and Technology, 2016

RECENT SCHOLAR PUBLICATIONS

  • Lumbar Spinal Stenosis Detection from Sagittal and Axial MR Images using Hybrid of Deep Kronecker Network and SpinalNet
    A Beulah
    European Spine Journal, 1-20 , 2025
    2025
  • MediaEval 2025: A Multimodal Approach for Predicting Movie and Commercial Memorability using Stacking and Gradient Boosting
    SMT Mariappan, M Ramasamy, B Arul
    2025
  • An EfficientNet Framework: Methods and Results for Synthetic Image Detection and Manipulation Localization
    SMT Mariappan, M Ramasamy, B Arul
    2025
  • Comparing CLIP-Based Image Retrieval and Stable Diffusion Turbo for News Article Thumbnails
    SMT Mariappan, M Ramasamy, B Arul
    2025
  • RECAIDSTechTitans at CLEF 2025: Simplifying Scientific Text and Identifying Spurious Sentences using T5
    E Stergio, A Beulah, V Sathvikha, V Sangamithra
    Conference and Labs of the Evaluation Forum (CLEF 2025) 4038 , 2025
    2025
  • REC_Cryptix at JOKER CLEF 2025: Teaching Machines to Laugh: Multilingual Humor Detection and Translation
    P Sarath Kumar, A Beulah, M Sushmitha, S Thanalaxmi
    Conference and Labs of the Evaluation Forum (CLEF 2025) 4038 , 2025
    2025
  • ImageCLEF-Medical 2025: MedCLIP Model for Medical Caption Prediction and Concept Detection
    SMT Mariappan, B Arul, M Ramasamy
    2025
  • Multi Disease Diagnostic Analysis for Chest X-Ray Images with Explainable AI
    R Priyadharsini, A Beulah, HP Prithika Priyadharshini, SB Rudrashree
    Communications on Applied Nonlinear Analysis 32 (10) , 2025
    2025
  • AirStrum: A virtual guitar using real-time hand gesture recognition and strumming technique.
    A Beulah, Shashank, Panda, N Tushar
    Romanian Journal of Information Technology & Automatic Control/Revista … , 2024
    2024
  • Diagnosis of central canal spinal stenosis from lumbar mid-sagittal mr images
    A Beulah, TS Sharmila, VK Pramod
    2024 International Conference on Advances in Computing, Communication and … , 2024
    2024
    Citations: 1
  • Cell classification in microscopic images for anemia detection
    P RAVISANKAR, A Beulah, S ELANGO
    Romanian Journal of Information Technology and Automatic Control 34 (1), 7-12 , 2024
    2024
    Citations: 1
  • Java code obfuscator to prevent reverse engineering of android application
    H Parandaman, B Arul, L Dinakaran
    AIP Conference Proceedings 2790 (1), 020004 , 2023
    2023
    Citations: 1
  • Degenerative disc disease diagnosis from lumbar MR images using hybrid features
    A Beulah, TS Sharmila, VK Pramod
    The Visual Computer 38 (8), 2771-2783 , 2022
    2022
    Citations: 22
  • Identification of Sickle Cells in Erythrocytes Images Using Shape
    L Yaminia, R Priyadharsinib, A Beulahc
    Smart Intelligent Computing and Communication Technology 38, 20 , 2021
    2021
  • Optimized image edge detection approach using fractional order calculus
    SK Srinithyee, E Srivarsha
    2021 6th International Conference on Communication and Electronics Systems … , 2021
    2021
    Citations: 5
  • Detection of electronic devices in real images using deep learning techniques
    G Krijeshan, P Raghul, NN Nachiappan
    2021 5th International Conference on Computer, Communication and Signal … , 2021
    2021
    Citations: 6
  • Home security system for the hearing impaired
    T Sneha, S Balasubramanian, SA Deborah
    2021 5th International Conference on Computer, Communication and Signal … , 2021
    2021
    Citations: 6
  • Spinal cord segmentation in lumbar mr images
    A Beulah, T Sree Sharmila, T Kanmani
    International Conference on Emerging Current Trends in Computing and Expert … , 2019
    2019
    Citations: 5
  • Disc bulge diagnostic model in axial lumbar MR images using Intervertebral disc Descriptor (IdD)
    A Beulah, TS Sharmila, VK Pramod
    Multimedia Tools and Applications 77 (20), 27215-27230 , 2018
    2018
    Citations: 26
  • Optic disc and cup segmentation in fundus retinal images using feature detection and morphological techniques
    R Priyadharsini, A Beulah, TS Sharmila
    Current science 115 (4), 752 , 2018
    2018
    Citations: 16

MOST CITED SCHOLAR PUBLICATIONS

  • Disc bulge diagnostic model in axial lumbar MR images using Intervertebral disc Descriptor (IdD)
    A Beulah, TS Sharmila, VK Pramod
    Multimedia Tools and Applications 77 (20), 27215-27230 , 2018
    2018
    Citations: 26
  • Degenerative disc disease diagnosis from lumbar MR images using hybrid features
    A Beulah, TS Sharmila, VK Pramod
    The Visual Computer 38 (8), 2771-2783 , 2022
    2022
    Citations: 22
  • Optic disc and cup segmentation in fundus retinal images using feature detection and morphological techniques
    R Priyadharsini, A Beulah, TS Sharmila
    Current science 115 (4), 752 , 2018
    2018
    Citations: 16
  • Detection of electronic devices in real images using deep learning techniques
    G Krijeshan, P Raghul, NN Nachiappan
    2021 5th International Conference on Computer, Communication and Signal … , 2021
    2021
    Citations: 6
  • Home security system for the hearing impaired
    T Sneha, S Balasubramanian, SA Deborah
    2021 5th International Conference on Computer, Communication and Signal … , 2021
    2021
    Citations: 6
  • Classification of intervertebral disc on lumbar MR images using SVM
    A Beulah, TS Sharmila
    2016 2nd international conference on applied and theoretical computing and … , 2016
    2016
    Citations: 6
  • Optimized image edge detection approach using fractional order calculus
    SK Srinithyee, E Srivarsha
    2021 6th International Conference on Communication and Electronics Systems … , 2021
    2021
    Citations: 5
  • Spinal cord segmentation in lumbar mr images
    A Beulah, T Sree Sharmila, T Kanmani
    International Conference on Emerging Current Trends in Computing and Expert … , 2019
    2019
    Citations: 5
  • EM algorithm based intervertebral disc segmentation on MR images
    A Beulah, TS Sharmila
    2017 International Conference on Computer, Communication and Signal … , 2017
    2017
    Citations: 5
  • Lumbar spine classification using pyramidal histogram of oriented gradients
    A Beulah, BK Divya Bharathi
    Indian Journal of Science and Technology 9 (32), 1-5 , 2016
    2016
    Citations: 2
  • Diagnosis of central canal spinal stenosis from lumbar mid-sagittal mr images
    A Beulah, TS Sharmila, VK Pramod
    2024 International Conference on Advances in Computing, Communication and … , 2024
    2024
    Citations: 1
  • Cell classification in microscopic images for anemia detection
    P RAVISANKAR, A Beulah, S ELANGO
    Romanian Journal of Information Technology and Automatic Control 34 (1), 7-12 , 2024
    2024
    Citations: 1
  • Java code obfuscator to prevent reverse engineering of android application
    H Parandaman, B Arul, L Dinakaran
    AIP Conference Proceedings 2790 (1), 020004 , 2023
    2023
    Citations: 1
  • Lumbar Spinal Stenosis Detection from Sagittal and Axial MR Images using Hybrid of Deep Kronecker Network and SpinalNet
    A Beulah
    European Spine Journal, 1-20 , 2025
    2025
  • MediaEval 2025: A Multimodal Approach for Predicting Movie and Commercial Memorability using Stacking and Gradient Boosting
    SMT Mariappan, M Ramasamy, B Arul
    2025
  • An EfficientNet Framework: Methods and Results for Synthetic Image Detection and Manipulation Localization
    SMT Mariappan, M Ramasamy, B Arul
    2025
  • Comparing CLIP-Based Image Retrieval and Stable Diffusion Turbo for News Article Thumbnails
    SMT Mariappan, M Ramasamy, B Arul
    2025
  • RECAIDSTechTitans at CLEF 2025: Simplifying Scientific Text and Identifying Spurious Sentences using T5
    E Stergio, A Beulah, V Sathvikha, V Sangamithra
    Conference and Labs of the Evaluation Forum (CLEF 2025) 4038 , 2025
    2025
  • REC_Cryptix at JOKER CLEF 2025: Teaching Machines to Laugh: Multilingual Humor Detection and Translation
    P Sarath Kumar, A Beulah, M Sushmitha, S Thanalaxmi
    Conference and Labs of the Evaluation Forum (CLEF 2025) 4038 , 2025
    2025
  • ImageCLEF-Medical 2025: MedCLIP Model for Medical Caption Prediction and Concept Detection
    SMT Mariappan, B Arul, M Ramasamy
    2025