Susama Bagchi

@chitkara.edu.in

Head Academic Delivery and Associate Professor, CSE Department, Chitkara University Institute of Engineering and Technology
Chitkara University, Punjab, India

Susama Bagchi


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https://researchid.co/bagchisusama

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Computer Engineering, Cancer Research, Computer Vision and Pattern Recognition
51

Scopus Publications

570

Scholar Citations

15

Scholar h-index

22

Scholar i10-index

Scopus Publications

  • Analyzing Cyber Threats in Banking Sector and Their Effective Solution—A Review
    Ujjawal Kumar Tripathi, Susama Bagchi, Sanjoy Kumar Debnath, Mohd Norzali Bin Hj Mohd, Amirah Aisha Badrul Hisham, Gaganpreet Kaur
    Lecture Notes in Networks and Systems, 2026
  • Boruta-LSTMAE: Feature-Enhanced Depth Image Denoising for 3D Recognition
    Fawad Salam Khan, Noman Hasany, Muzammil Ahmad Khan, Shayan Abbas, Sajjad Ahmed, Muhammad Zorain, Wai Yie Leong, Susama Bagchi, Sanjoy Kumar Debnath
    Computers Materials and Continua, 2026
    The initial noise present in the depth images obtained with RGB-D sensors is a combination of hardware limitations in addition to the environmental factors, due to the limited capabilities of sensors, which also produce poor computer vision results. The common image denoising techniques tend to remove significant image details and also remove noise, provided they are based on space and frequency filtering. The updated framework presented in this paper is a novel denoising model that makes use of Boruta-driven feature selection using a Long Short-Term Memory Autoencoder (LSTMAE). The Boruta algorithm identifies the most useful depth features that are used to maximize the spatial structure integrity and reduce redundancy. An LSTMAE is then used to process these selected features and model depth pixel sequences to generate robust, noise-resistant representations. The system uses the encoder to encode the input data into a latent space that has been compressed before it is decoded to retrieve the clean image. Experiments on a benchmark data set show that the suggested technique attains a PSNR of 45 dB and an SSIM of 0.90, which is 10 dB higher than the performance of conventional convolutional autoencoders and 15 times higher than that of the wavelet-based models. Moreover, the feature selection step will decrease the input dimensionality by 40%, resulting in a 37.5% reduction in training time and a real-time inference rate of 200 FPS. Boruta-LSTMAE framework, therefore, offers a highly efficient and scalable system for depth image denoising, with a high potential to be applied to close-range 3D systems, such as robotic manipulation and gesture-based interfaces.
  • Enhanced Intrusion Detection with Advanced Deep Features and Ensemble Classifier Techniques
    Pawan Toralkar, Kavita Mainalli, Shridhar Allagi, Sanjoy Kumar Debnath, Susama Bagchi, Wai Yie Leong, Muhammad Numan Ali Khan
    SN Computer Science, 2025
  • Photoplethysmography Bio-Signal Extraction for Classifying Diabetes Mellitus Diseases Using Pretrained Deep Learning Networks
    Syaidatus Syahira Ahmad Tarmizi, Nor Surayahani Suriani, Mohd Norzali Bin Hj Mohd, Susama Bagchi, Sanjoy Kumar Debnath, Syed Mehr Ali Shah
    SN Computer Science, 2025
  • Predicting Object Communication Errors in Constructor Development
    Abdul Majid Soomro, Awad Bin Naeem, Susama Bagchi, Babul Salam KSM Kader Ibrahim, Sanjoy Kumar Debnath
    IEEE Access, 2025
    An important challenge in dynamic software development is to predict object formation run-time object communication errors in complex environments involving multiple and multi-level object inheritance. This paper proposes a technique for doing so. The technique is intended to stop or fix software bugs, particularly in situations where it is believed that object communications would persist across different settings. The research addresses a critical gap in existing methodologies by integrating static and dynamic object-oriented metrics, providing a holistic approach to defect prediction. Additionally, the paper presents a software testing defect prediction model that categorizes problematic classes according to inheritance defects found in a particular class. Earlier researchers studied various methods for predicting and mitigating software defects in object-oriented programming. We propose a defect prediction model that categorizes problematic classes based on inheritance defects to overcome the gaps in existing methodologies by introducing them. We evaluated this object communication error prediction using a set of 150 common errors drawn primarily from real-world open-source repositories and enriched with synthesized cases reflecting rare but critical inheritance-related bugs, ensuring comprehensive and realistic error representation. The methodology employs classification techniques, including K-Nearest Neighbors (KNN) for k-fold cross-validation, Random Forest, Decision Trees, and Support Vector Machines (SVM), alongside object-oriented metrics such as inheritance, cohesion, and coupling. Key performance metrics precision (78%), F1 score (76.4%), recall (74.9%), and ROC AUC (89%), demonstrate the model’s superiority over prior approaches. These results underscore the practical applicability of the model in improving defect detection accuracy and reducing software failures.
  • Automated Lung Disease Classification Using Convolutional Neural Networks: A Study on Normal, Lung Opacity, and Viral Pneumonia Detection from Chest X-ray Images
    Jatin Sharma, Raghavendra Sridhar, Rashi Nimesh Kumar Dhenia, Ishva Jitendrakumar Kanani, Deepak Banerjee, Susama Bagchi
    2025 IEEE Madhya Pradesh Section Conference Mpcon 2025, 2025
    The objective is to develop a CNN system which classifies different lung illnesses based on chest X-ray images. Global health issues primarily focus on three types of lung disorders: normal lung problems, viral pneumonia and lung opacity where early diagnosis directs the treatment process. CNNs gain the ability to detect complex scans and X-rays because they automatically learn multidimensional features directly from primary image data. The improved medical image analysis efficiency becomes possible through this approach. The researchers initiated their experiment with three distinct image groups containing 3,475 X-ray images between Normal and Lung Opacity and Viral Pneumonia categories. These pictures move into different sets to ensure model generalization after they separate into training, validation and test groups. The pre-trained models such as ResNet50 and VGG16 allow transfer learning methods to train the suggested CNN model so it can detect meaningful information in limited dataset settings. The preprocessing methodologies for model performance boost include scaling and normalization alongside data augmentation techniques. The model reaches an overall accuracy of 91% with the most accurate identification of viral pneumonia. At low misclassification levels the model demonstrates a high capability to differentiate between viral pneumonia and lung opacity based on the confusion matrix analysis. The research demonstrates how CNNs can assist medical professionals to provide timely accurate medical treatment through advanced lung disease diagnosis accuracy rates.
  • Automated Sustainable Grading of Chali Arecanuts: A Machine Learning Approach to Quality Assurance
    Chinmai Shetty, Malathi S Y, Hareesh Inamdar, Gangothri Sanil, Susama Bagchi, Sanjoy Kumar Debnath
    2025 IEEE International Conference on Distributed Computing VLSI Electrical Circuits and Robotics Discover 2025 Proceedings, 2025
    This paper demonstrates an AI-driven method for automatically evaluating arecanuts using computer vision and machine learning approaches is presented in this study. Inconsistent quality assessment, work effort, and subjectivity are the common problems faced when opted for the manual grading techniques. Dataset comprising of more than <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{3, 7 0 0}$</tex> high-resolution images with white background in four quality grading was collected. Convolutional neural networks (CNNs) are used in the suggested system to evaluate important quality attributes as size, color, texture, and structural integrity. Several architectures were evaluated, including an ensemble approach that mixed Support Vector Machine (SVM) and Random Forest (RF), InceptionV3, ResNet50, EfficientNetB3. The study highlights real-world applicability by optimizing for low-resource hardware, energy economy, and operational simplicity, compared to traditional techniques, the approach provides significant improvements in processing speed and grading uniformly. Although previous studies have indicated good lab-level accuracy, issues such as field variability and a lack of standardized grading procedures still exist. The proposed work aims to improve production and guarantee consistent quality standards across farms by developing a scalable, affordable, and reliable precision agriculture solution.
  • Wearable intelligence system for health care: Synergizing smart devices and RNN-LSTM through IoT
    Gaganpreet Kaur, Anuj Kumar Jain, Nitin Jain, Sanjoy Kumar Debnath, Susama Bagchi, A.V. Senthil Kumar
    Computational Methods in Science and Technology Proceedings of the 4th International Conference on Computational Methods in Science and Technology Iccmst 2024, 2025
    The rapid advancement of technology has paved the way for transformative changes in the healthcare area. Fitness trackers and other smart wearables that can continuously gather a plethora of physiological data from users have become increasingly popular. The system creates a seamless connection amongst patients and healthcare professionals by utilizing the capabilities of these devices, enabling real-time data transmission and analysis. Data flow is coordinated by the intelligent IoT framework, which also ensures that the data is securely transmitted, stored, and retrieved. The proposed study creates a Wearable with the (IoT)-based integrated healthcare system for initial detection with higher performance. The suggested integrated healthcare system makes use of wearable technology and deep learning methods to improve patient monitoring, diagnosis, and treatment. To detect those individuals who are afflicted at an early stage before the illness advances, the system makes use of the WIoT based on Artificial Intelligence technology. The proposed wearable health care system uses RNN-LSTM to monitor the data collected. It achieves an accuracy of 93% at epoch is 60 and batch size for RNN-LSTM is 100.
  • Synchronous Buck Converter
    Dhananjaya B, Sadhana B, Sanjoy Kumar Debnath, Susama Bagchi, Amirah 'Aisha Badrul Hisham, Khalil Azha Mohd Annuar
    2025 International Conference on Emerging Technologies in Engineering Applications Icetea 2025 Proceedings, 2025
    Step down converters, also referred to as Buck converters, are used in a variety of applications, including management of power and voltage regulator modules (VRMs), to reduce the DC input voltage. A MOSFET, which offers a low resistance route, is used in place of the free-wheeling diode in a Synchronous Buck converter to lower the conduction losses. But this makes the gate drive circuitry more complicated. This work designs a synchronous buck converter, investigates how it works, and assesses how well it performs in terms of efficiency increase when compared to a typical buck converter that operates at a high switching frequency of 200 kHz. Both synchronous and conventional buck converters can generate up to 1A of current and are made to provide a 5V DC output from a 12V DC supply. The circuit is simulated using Matlab/Simulink. The outcomes of the simulation and the real-world circuits are evaluated and contrasted.
  • Affordable Autonomous Driving System using Arduino Uno
    Dhananjaya B, Sadhana B, Sanjoy Kumar Debnath, Susama Bagchi, Kamal Saluja, Amirah ‘Aisha Badrul Hisham
    Proceedings of 5th International Conference on Trends in Material Science and Inventive Materials Ictmim 2025, 2025
    An autonomous vehicle is one that can travel and complete its functions without the assistance of an operator. There are three main types of autonomous vehicles: air, ground, and submersible. They are a relatively new subset of robotics. They can be used in a number of scenarios when it would be unsafe, impractical, or impossible to have a human operator present. The car will be equipped with of sensors to monitor the ambience and make decisions regarding its own actions. A human controller is not necessary for an autonomous vehicle to function. Through the use of its sensors, the vehicle gains a limited understanding of its surroundings, which control algorithms utilize to decide what to do next in relation to a mission goal that is supplied by the human. This completely removes the necessity for any person to keep an eye on the mundane duties that the car is performing.
  • Diagnosis of Autoimmune Thrombocytopenic Disease by Using an Adaptive Genetic Algorithm
    Abdul Majid Soomro, Sanjoy Kumar Debnath, Jatin Arora, Kamal Saluja, Susama Bagchi, Awad Bin Naeem, Chinmai Shetty
    Lecture Notes in Networks and Systems, 2025
  • Improvement in Rare Attack Intrusion Detection Rate Using Machine Learning Algorithms
    Abdul Majid Soomro, Ahmad Waleed, Susama Bagchi, Sanjoy Kumar Debnath, Shruti Arora, Swati Malik, Gaganpreet Kaur
    Lecture Notes in Networks and Systems, 2025
  • Responsive Home for Emotion Regulation Applications with Convolutional Neural Network
    Cheng Hong Hew, Mastaneh Mokayef, M. K. A. Ahamed Khan, MHD Amen Summakieh, Susama Bagchi, Sanjoy Kumar Debnath, D.Najumnissa Jamal, Kalaiselvi Aramugam
    Proceedings 2025 Asia Conference on Energy Conversion Systems and Power Electronics Aecspe 2025, 2025
  • Evaluation of Heart Disease Risk Using Deep Learning Technique with Image Enhancement
    Proceedings of International Conference on Artificial Life and Robotics, 2025
  • Potato Leaf Disease Classification Using Transfer Learning with VGG16 on an Expert-Annotated Field Dataset
    Journal of Robotics Networking and Artificial Life, 2025
  • An Innovative Deep Learning Technique to Identify Potato Illness
    Proceedings of International Conference on Artificial Life and Robotics, 2025
  • A Floor Tiling Robotic System
    Proceedings of International Conference on Artificial Life and Robotics, 2025
  • A Wearable Walking Support System Design and Simulation
    Proceedings of International Conference on Artificial Life and Robotics, 2025
  • Big Bang theory improved shortest path, construction, evolution and status model based course like environment machine learning
    Tejinder Kaur, Abhijeet Singh, Yuvraj Singh Behl, Sanjoy Kumar Debnath, Susama Bagchi
    Artificial Intelligence Blockchain Computing and Security Proceedings of the International Conference on Artificial Intelligence Blockchain Computing and Security Icabcs 2023, 2024
  • A Study of Dual Active Bridge Converter Performance
    Dhananjaya B, Sadhana B, Susama Bagchi, Sanjoy Kumar Debnath, Tapan Kumar Chakraborty, Manika Debnath
    2024 Asia Pacific Conference on Innovation in Technology Apcit 2024, 2024
  • Naive Bayes Classifier-Based Smishing Detection Framework to Reduce Cyber Attack
    Gaganpreet Kaur, Kiran Deep Singh, Jatin Arora, Susama Bagchi, Sanjoy Kumar Debnath, A. V. Senthil Kumar
    Lecture Notes in Networks and Systems, 2024
  • Exploring Robust DDoS Detection: A Machine Learning Analysis with the CICDDoS2019 Dataset
    Kamal Saluja, Susama Bagchi, Vikas Solanki, Muhammad Numan Ali Khan, Esha Dhamija, Sanjoy Kumar Debnath
    Indiscon 2024 5th IEEE India Council International Subsections Conference Science Technology and Society, 2024
  • Deep Learning Approaches for Cataract Detection Using Fundus and Real-Time Naked Eye Imaging
    Chinmai Shetty, Shainy Fernandes, Susama Bagchi, S Y Malathi, Subrahmanya Rajesh Nayak, Sanjoy Kumar Debnath
    IEEE International Conference on Recent Advances in Science and Engineering Technology Icraset 2024, 2024
  • A Scalable Approach to Counter Reliability and Load Balancing in Mobile Wireless Sensor Networks
    Siddharth Kumar, Alankrita Aggarwal, Rattan Deep Aneja, Susama Bagchi, Sanjoy Kumar Debnath, Syed Mehr Ali Shah
    1st International Conference on Innovative Engineering Sciences and Technological Research Iciestr 2024 Proceedings, 2024
  • Two-Level Secure Framework for Authentication System for Embedded Systems
    Gaganpreet Kaur, Kiran Deep Singh, Jatin Arora, Susama Bagchi, Sanjoy Kumar Debnath, A. V. Senthil Kumar
    Smart Innovation Systems and Technologies, 2024
  • Detection of food allergy using deep learning
    Medical Imaging Informatics Machine Learning Deep Learning and Big Data Analytics, 2024
  • Improved Gastric Cancer Diagnosis with Machine Learning Technique: Addressing Imbalanced Data Distribution
    Danish Jamil, Susama Bagchi, Sanjoy Kumar Debnath, Swati Malik, Gaganpreet Kaur, Monika Sethi, Muhammad Numan Ali Khan
    Smart Innovation Systems and Technologies, 2024
  • A thorough analysis on mitigating the risk of gastric cancer using proper nutrition
    Danish Jamil, Sellappan Palaniappan, Sanjoy Kumar Debnath, Susama Bagchi, Sunil Kumar Chawla, Tejinder Kaur, Ankit Bansal
    Securing Next Generation Connected Healthcare Systems Artificial Intelligence Technologies, 2024
  • Big Bang theory improved shortest path, construction, evolution and status model based course like environment machine learning
    Tejinder Kaur, Abhijeet Singh, Yuvraj Singh Behl, Sanjoy Kumar Debnath, Susama Bagchi
    Artificial Intelligence Blockchain Computing and Security Volume 1, 2023
  • Uncovering Spam in Twitter: A Machine Learning Approach
    Abdul Majid Soomro, Awad Bin Naeem, Susama Bagchi, Neha Sharma, Pardeep Singh, Sanjoy Kumar Debnath
    Proceedings of International Conference on Computational Intelligence and Sustainable Engineering Solution Cises 2023, 2023
  • Private Cloud Hybrid Architecture for Protected Data Communication
    Abdul Majid Soomro, Awad Bin Naeem, Sanjoy Kumar Debnath, Susama Bagchi, Sunil Gupta, Kamal Saluja
    2023 International Conference on Advancement in Computation and Computer Technologies Incacct 2023, 2023
  • Intrusion Detection Behavioral Model by Using ANN
    Abdul Majid Soomro, Sanjoy Kumar Debnath, Awad Bin Naeem, Susama Bagchi, Kamal Saluja, Sunil Gupta
    Lecture Notes in Networks and Systems, 2023
  • Cyber Security Architecture for Safe Data Storage and Retrieval for Smart City Applications
    Ritu Tyagi, Susama Bagchi, Gaganpreet Kaur, Neha Sharma, Muhammad Numan Ali Khan, Chander Prabha
    Proceedings of International Conference on Computational Intelligence and Sustainable Engineering Solution Cises 2023, 2023
  • Prediction Accuracy Improvement for Cardiovascular Diseases Using Machine Learning Algorithm
    Sanjoy Kumar Debnath, Swati Malik, Gaganpreet Kaur, Susama Bagchi, Abdul Majid Soomro, Awad Naeem
    2023 10th IEEE Uttar Pradesh Section International Conference on Electrical Electronics and Computer Engineering Upcon 2023, 2023
  • A feedback controller for milling chatter vibration control using a new response matrix
    Bashir B Muhammad, Muhammad Bashir, Mukhtar F Hamza, Mustapha Abdulhadi, Muhammad A Shehu, Sanjoy K Debnath, Susama Bagchi
    JVC Journal of Vibration and Control, 2022
  • EXPERIMENTAL STUDY ON SURFACE MORPHOLOGY, DENSITY AND RELATIVE DIELECTRIC CONSTANT OF HIGH-DENSITY POLYETHYLENE (HDPE)/NATURAL RUBBER (NR) BIOCOMPOSITES
    Universiti Tun Hussein Onn Malaysia (UTHM), MOHD HARIS ASYRAF SHEE KANDAR, NOR AKMAL MOHD JAMAIL, Universiti Tun Hussein Onn Malaysia (UTHM), SUSAMA BAGCHI, Universiti Tun Hussein Onn Malaysia (UTHM), NOR SHAHIDA MOHD JAMAIL, Prince Sultan University (PSU), RAHISHAM ABD RAHMAN, Universiti Tun Hussein Onn Malaysia (UTHM), QAMARUL EZANI KAMARUDIN, Universiti Tun Hussein Onn Malaysia (UTHM), FAHMIRUDDIN ESA, Universiti Tun Hussein Onn Malaysia (UTHM), SANJOY KUMAR DEBNATH, Universiti Tun Hussein Onn Malaysia (UTHM)
    Journal of Sustainability Science and Management, 2022
  • Block Chain Technology for Limiting the Impact of Pandemic: Open Issues and Challenges
    Tejinder Kaur, Susama Bagchi, Sanjoy Kumar Debnath, Jayashree Mohanty
    Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology Ccet 2022, 2022
  • Artificial Intelligence Application for Security Issues and Challenges in IoT
    Chetna Vaid Kwatra, Anupam Jain, Angelina Royappa, Susama Bagchi, S B G Tilak Babu, Harish Chowdhary
    Proceedings of 5th International Conference on Contemporary Computing and Informatics Ic3i 2022, 2022
  • 3D Hand Gestures Segmentation and Optimized Classification Using Deep Learning
    Fawad Salam Khan, Mohd Norzali Haji Mohd, Dur Muhammad Soomro, Susama Bagchi, M. Danial Khan
    IEEE Access, 2021
  • A Smart Flight Controller based on Reinforcement Learning for Unmanned Aerial Vehicle (UAV)
    Fawad Salam Khan, Mohd Norzali Haji Mohd, Raja Masood Larik, Muhammad Danial Khan, Muhammad Inam Abbasi, Susama Bagchi
    Proceedings of the 2021 IEEE International Conference on Signal and Image Processing Applications Icsipa 2021, 2021
  • Fetal ECG Extraction from Abdominal ECG Using Chebyshev and Butterworth Filters
    Shaun Eng Shuen Gan, Sanjoy Kumar Debnath, Yousif Saad Alshebly, Hermawan Nugroho, Susama Bagchi, Marwan Nafea
    Isci 2021 2021 IEEE Symposium on Computers and Informatics, 2021
  • Different cell decomposition path planning methods for unmanned air vehicles-a review
    Sanjoy Kumar Debnath, Rosli Omar, Susama Bagchi, Elia Nadira Sabudin, Mohd Haris Asyraf Shee Kandar, Khan Foysol, Tapan Kumar Chakraborty
    Lecture Notes in Electrical Engineering, 2021
  • Computationally efficient path planning algorithm for autonomous vehicle
    Sanjoy Kumar Debnath, Rosli Omar, Nor Badariyah Abdul Latip, Susama Bagchi, Elia Nadira Sabudin, Abdul Rashid Omar Mumin, Abdul Majid Soomro, Marwan Nafea, Bashir Bala Muhammad, Ranesh Kumar Naha
    Jurnal Teknologi, 2021
  • Review of space charge measurement by pulsed electro-acoustic technique
    Mohd Haris Asyraf Shee Kandar, Nor Akmal Mohd Jamail, Nordiana Azlin Othman, Qamarul Ezani Kamarudin, Nor Shahida Mohd Jamail, Susama Bagchi
    Indonesian Journal of Electrical Engineering and Computer Science, 2020
  • Hybrid Hysteresis-Inversion and PSO-Tuned PID Control for Piezoelectric Micropositioning Stages
    Shadir Ahamed Mohamed Rifai, Marwan Nafea, Sanjoy Kumar Debnath, Susama Bagchi
    2020 IEEE Student Conference on Research and Development Scored 2020, 2020
  • Breast Cancer Histological Images Nuclei Segmentation using Mask Regional Convolutional Neural Network
    Fawad Salam Khan, Mohd Norzali Haji Mohd, Muhammad Danial Khan, Susama Bagchi
    2020 IEEE Student Conference on Research and Development Scored 2020, 2020
  • Performance Comparison of Pre-trained Residual Networks for Classification of the Whole Mammograms with Smaller Dataset
    Susama Bagchi, Mohd Norzali Haji Mohd, Sanjoy Kumar Debnath, Marwan Nafea, Nor Surayahani Suriani, Yoosuf Nizam
    2020 IEEE Student Conference on Research and Development Scored 2020, 2020
  • Image processing and machine learning techniques used in computer-aided detection system for mammogram screening-A review
    Susama Bagchi, Kim Gaik Tay, Audrey Huong, Sanjoy Kumar Debnath
    International Journal of Electrical and Computer Engineering, 2020
  • Energy Efficient Elliptical Concave Visibility Graph Algorithm for Unmanned Aerial Vehicle in an Obstacle-rich Environment
    Sanjoy Kumar Debnath, Rosli Omar, Susama Bagchi, Marwan Nafea, Ranesh Kumar Naha, Elia Nadira Sabudin
    2020 IEEE International Conference on Automatic Control and Intelligent Systems I2cacis 2020 Proceedings, 2020
  • Flight cost calculation for unmanned air vehicle based on path length and heading angle change
    Sanjoy Kumar Debnath, Rosli Omar, B.S.S.K. Ibrahim, Susama Bagchi, Elia Nadira, Faisal Amin, Bashir Bala Muhammad
    International Journal of Power Electronics and Drive Systems, 2020
  • Investigation of different spatial filters performance toward mammogram de-noising
    International Journal of Integrated Engineering, 2017

RECENT SCHOLAR PUBLICATIONS

  • Boruta-LSTMAE: Feature-Enhanced Depth Image Denoising for 3D Recognition
    FS Khan, N Hasany, MA Khan, S Abbas, S Ahmed, M Zorain, WY Leong, ...
    2026
  • Automated Sustainable Grading of Chali Arecanuts: A Machine Learning Approach to Quality Assurance
    C Shetty, SY Malathi, H Inamdar, G Sanil, S Bagchi, SK Debnath
    2025 IEEE International Conference on Distributed Computing, VLSI … , 2025
    2025
  • Responsive Home for Emotion Regulation Applications with Convolutional Neural Network
    CH Hew, M Mokayef, MKAA Khan, MHDA Summakieh, S Bagchi, ...
    2025 Asia Conference on Energy Conversion Systems and Power Electronics … , 2025
    2025
  • Automated Lung Disease Classification Using Convolutional Neural Networks: A Study on Normal, Lung Opacity, and Viral Pneumonia Detection from Chest X-ray Images
    J Sharma, R Sridhar, RNK Dhenia, IJ Kanani, D Banerjee, S Bagchi
    2025 IEEE Madhya Pradesh Section Conference (MPCON), 601-605 , 2025
    2025
  • Predicting Object Communication Errors in Constructor Development
    AM Soomro, AB Naeem, S Bagchi, BSKSMK Ibrahim, SK Debnath
    IEEE Access , 2025
    2025
  • Analyzing Cyber Threats in Banking Sector and Their Effective Solution—A Review
    UK Tripathi, S Bagchi, SK Debnath, MN Bin Hj Mohd, AA Badrul Hisham, ...
    International Conference on Computational Intelligence and Information … , 2025
    2025
  • Enhanced Intrusion Detection with Advanced Deep Features and Ensemble Classifier Techniques
    P Toralkar, K Mainalli, S Allagi, SK Debnath, S Bagchi, WY Leong, ...
    SN Computer Science 6 (4), 381 , 2025
    2025
    Citations: 7
  • Evaluation of Heart Disease Risk Using Deep Learning Technique with Image Enhancement
    SA Majid, A Asad, B Susama, DS Kumar, N Awad, KMKA Ahamed, ...
    人工生命とロボットに関する国際会議予稿集 30, 710-716 , 2025
    2025
  • An Innovative Deep Learning Technique to Identify Potato Illness
    SA Majid, AM Haseeb, DS Kumar, B Susama, N Awad, KMKA Ahamed, ...
    人工生命とロボットに関する国際会議予稿集 30, 688-694 , 2025
    2025
  • A Wearable Walking Support System Design and Simulation
    YO Ayaman, KMKA Ahamed, M Mastaneh, A Ridzuan, Q Abdul, M Moona, ...
    人工生命とロボットに関する国際会議予稿集 30, 695-701 , 2025
    2025
  • A Floor Tiling Robotic System
    JH Chau, KMKA Ahamed, M Mastaneh, A Ridzuan, Q Abdul, M Moona, ...
    人工生命とロボットに関する国際会議予稿集 30, 702-709 , 2025
    2025
  • Photoplethysmography Bio-Signal Extraction for Classifying Diabetes Mellitus Diseases Using Pretrained Deep Learning Networks
    SSA Tarmizi, NS Suriani, MNBH Mohd, S Bagchi, SK Debnath, SMA Shah
    SN Computer Science 6 (2), 104 , 2025
    2025
    Citations: 10
  • Potato Leaf Disease Classification Using Transfer Learning with VGG16 on an Expert-Annotated Field Dataset
    AM Soomro, MH Asghar, S Bagchi, SK Debnath, AK MKA, M Mokayef, ...
    Journal of Robotics, Networking and Artificial Life 11 (2), 152-159 , 2025
    2025
  • A Floor Tiling Robotic System
    HC Jieng, MKAA Khan, M Mokayef, ARB Abd Hamid, A Qayyum, ...
    2025
    Citations: 1
  • Deep Learning Approaches for Cataract Detection Using Fundus and Real-Time Naked Eye Imaging
    C Shetty, S Fernandes, S Bagchi, SY Malathi, SR Nayak, SK Debnath
    2024 International Conference on Recent Advances in Science and Engineering … , 2024
    2024
    Citations: 1
  • Wearable intelligence system for health care: Synergizing smart devices and RNN-LSTM through IoT
    G Kaur, AK Jain, N Jain, SK Debnath, S Bagchi, AVS Kumar
    Computational Methods in Science and Technology, 114-121 , 2024
    2024
    Citations: 15
  • Improved Gastric Cancer Diagnosis with Machine Learning Technique: Addressing Imbalanced Data
    D Jamil, S Bagchi, SK Debnath, S Malik
    Smart Systems: Innovations in Computing: Proceedings of SSIC 2023, 211 , 2024
    2024
    Citations: 12
  • Exploring Robust DDoS Detection: A Machine Learning Analysis with the CICDDoS2019 Dataset
    K Saluja, S Bagchi, V Solanki, MNA Khan, E Dhamija, SK Debnath
    2024 IEEE 5th India Council International Subsections Conference (INDISCON), 1-6 , 2024
    2024
    Citations: 11
  • A Study of Dual Active Bridge Converter Performance
    B Dhananjaya, B Sadhana, S Bagchi, SK Debnath, TK Chakraborty, ...
    2024 Asia Pacific Conference on Innovation in Technology (APCIT), 1-7 , 2024
    2024
    Citations: 4
  • Improvement in Rare Attack Intrusion Detection Rate Using Machine Learning Algorithms
    AM Soomro, A Waleed, S Bagchi, SK Debnath, S Arora, S Malik, G Kaur
    International Conference on Data Analytics and Insights, 367-377 , 2024
    2024

MOST CITED SCHOLAR PUBLICATIONS

  • Different cell decomposition path planning methods for unmanned air vehicles-a review
    SK Debnath, R Omar, S Bagchi, EN Sabudin, MHA Shee Kandar, ...
    National Technical Seminar on Unmanned System Technology, 99-111 , 2019
    2019
    Citations: 62
  • Image processing and machine learning techniques used in computer-aided detection system for mammogram screening-A review
    S Bagchi, KG Tay, A Huong, SK Debnath
    International Journal of Electrical and Computer Engineering (IJECE) 10 (3 … , 2020
    2020
    Citations: 60
  • 3D Hand Gestures Segmentation and Optimized Classification Using Deep Learning
    FS Khan, MNH Mohd, DM Soomro, S Bagchi, MD Khan
    IEEE Access 9, 131614-131624 , 2021
    2021
    Citations: 35
  • Signal Processing Techniques and Computer-Aided Detection Systems for Diagnosis of Breast Cancer –A Review Paper
    S Bagchi, A Huong
    Indian Journal of Science and Technology , 2017
    2017
    Citations: 32
  • Performance Comparison of Pre-trained Residual Networks for Classification of the Whole Mammograms with Smaller Dataset
    S Bagchi, MNH Mohd, SK Debnath, M Nafea, NS Suriani, Y Nizam
    2020 IEEE Student Conference on Research and Development (SCOReD), 368-373 , 2020
    2020
    Citations: 24
  • Computationally efficient path planning algorithm for autonomous vehicle
    SK Debnath, R Omar, NBA Latip, S Bagchi, EN Sabudin, ARO Mumin, ...
    Jurnal Teknologi (Sciences & Engineering) 83 (1), 133-143 , 2020
    2020
    Citations: 22
  • Hybrid hysteresis-inversion and PSO-tuned PID control for piezoelectric micropositioning stages
    SAM Rifai, M Nafea, SK Debnath, S Bagchi
    2020 IEEE Student Conference on Research and Development (SCOReD), 206-210 , 2020
    2020
    Citations: 22
  • Energy efficient elliptical concave visibility graph algorithm for unmanned aerial vehicle in an obstacle-rich environment
    SK Debnath, R Omar, S Bagchi, M Nafea, RK Naha, EN Sabudin
    2020 IEEE international conference on automatic control and intelligent … , 2020
    2020
    Citations: 22
  • Artificial Intelligence Application for Security Issues and Challenges in IoT
    CV Kwatra, A Jain, A Royappa, S Bagchi, SBGT Babu, H Chowdhary
    2022 5th International Conference on Contemporary Computing and Informatics … , 2022
    2022
    Citations: 20
  • Block Chain Technology for Limiting the Impact of Pandemic: Open Issues and Challenges
    T Kaur, S Bagchi, SK Debnath, J Mohanty
    2022 IEEE International Conference on Current Development in Engineering and … , 2022
    2022
    Citations: 19
  • Breast cancer histological images nuclei segmentation using mask regional convolutional neural network
    FS Khan, MNH Mohd, MD Khan, S Bagchi
    2020 IEEE Student Conference on Research and Development (SCOReD), 1-6 , 2020
    2020
    Citations: 18
  • Flight cost calculation for unmanned air vehicle based on path length and heading angle change
    SK Debnath, R Omar, B Ibrahim, S Bagchi, E Nadira, F Amin, ...
    Int J Pow Elec & Dri Syst ISSN 2088 (8694), 8694 , 2020
    2020
    Citations: 18
  • Investigation of different spatial filters performance toward mammogram de-noising
    S Bagchi, A Huong, KG Tay
    Int. J. Integr. Eng 9 (3), 49-53 , 2017
    2017
    Citations: 18
  • Intrusion Detection Behavioral Model by Using ANN
    AM Soomro, SK Debnath, AB Naeem, S Bagchi, K Saluja, S Gupta
    International Conference on Data Analytics and Insights, 589-600 , 2023
    2023
    Citations: 16
  • A feedback controller for milling chatter vibration control using a new response matrix
    BB Muhammad, M Bashir, MF Hamza, M Abdulhadi, MA Shehu, ...
    Journal of Vibration and Control 28 (9-10), 998-1010 , 2022
    2022
    Citations: 16
  • Wearable intelligence system for health care: Synergizing smart devices and RNN-LSTM through IoT
    G Kaur, AK Jain, N Jain, SK Debnath, S Bagchi, AVS Kumar
    Computational Methods in Science and Technology, 114-121 , 2024
    2024
    Citations: 15
  • Cyber Security Architecture for Safe Data Storage and Retrieval for Smart City Applications
    R Tyagi, S Bagchi, G Kaur, N Sharma, MNA Khan, C Prabha
    2023 International Conference on Computational Intelligence and Sustainable … , 2023
    2023
    Citations: 14
  • Improved Gastric Cancer Diagnosis with Machine Learning Technique: Addressing Imbalanced Data
    D Jamil, S Bagchi, SK Debnath, S Malik
    Smart Systems: Innovations in Computing: Proceedings of SSIC 2023, 211 , 2024
    2024
    Citations: 12
  • Exploring Robust DDoS Detection: A Machine Learning Analysis with the CICDDoS2019 Dataset
    K Saluja, S Bagchi, V Solanki, MNA Khan, E Dhamija, SK Debnath
    2024 IEEE 5th India Council International Subsections Conference (INDISCON), 1-6 , 2024
    2024
    Citations: 11
  • Fetal ECG Extraction from Abdominal ECG Using Chebyshev and Butterworth Filters
    SES Gan, SK Debnath, YS Alshebly, H Nugroho, S Bagchi, M Nafea
    2021 IEEE Symposium on Computers & Informatics (ISCI), 25-30 , 2021
    2021
    Citations: 11