H
Hari Mohan Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor Research
faculty
19 h-index
125 pubs
1,620 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Dr. Hari Mohan Rai's research focuses on the application of deep learning and machine learning techniques for medical image analysis and disease detection. His work frequently involves developing and evaluating novel hybrid deep convolutional neural network (CNN) models, such as CNN-LSTM and UnetResNext-50, to improve the accuracy and efficiency of diagnostic processes.
His recent publications demonstrate a strong emphasis on using these advanced computational methods for identifying cardiac abnormalities from electrocardiogram (ECG) data and detecting brain tumors from MRI images. He has also contributed to the review of recent advancements in machine learning and deep learning for cancer detection and segmentation, highlighting their role in improving diagnostic techniques across various biomedical imaging datasets.
Dr. Rai's scholarly contributions include over 125 total publications, with 19 recognized by an h-index of 19 and 1,620 total citations. He has also held academic positions in institutions across South Korea, Kazakhstan, and India, and has actively participated in organizing international conferences. His collaborators include Abdul Razaque from Arkansas Tech University, with whom he has co-authored three publications.
Metrics
- h-index: 19
- Publications: 125
- Citations: 1,620
Selected Publications
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HAttFFNN: Hybridized attention mechanism-based feedforward neural network deep learning model for the plastic material classification of three stage materials on spectroscopic data (2025)
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ViT-DCNN: Vision Transformer with Deformable CNN Model for Lung and Colon Cancer Detection (2025)
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Vehicle tracking and classification for intelligent transportation systems using YOLOv5 and modified deep SORT with HRNN (2025)
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Computational Intelligence Transforming Healthcare 4.0: Innovations in Medical Image Analysis through AI and IoT Integration (2025)
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Deep Learning for Leukemia Classification: Performance Analysis and Challenges Across Multiple Architectures (2025)
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Advanced AI-Powered Intrusion Detection Systems in Cybersecurity Protocols for Network Protection (2025)
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Shaping the Future with Quantum Computing: An Exploration of its Emerging Field and Revolutionary Potential (2025)
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Optimizing Financial Planning Through Advanced Machine Learning Techniques (2025)
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SwinConvNeXt: a fused deep learning architecture for Real-time garbage image classification (2025)
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LightweightUNet: Multimodal Deep Learning with GAN-Augmented Imaging Data for Efficient Breast Cancer Detection (2025)
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Transformative Advances in AI for Precise Cancer Detection: A Comprehensive Review of Non-Invasive Techniques (2025)
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The Improved Network Intrusion Detection Techniques Using the Feature Engineering Approach with Boosting Classifiers (2024)
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Transformative impacts of AI and the IoT on healthcare delivery (2024)
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Advanced Segmentation of Gastrointestinal (GI) Cancer Disease Using a Novel U-MaskNet Model (2024)
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Advanced Noise-Resistant Electrocardiography Classification Using Hybrid Wavelet-Median Denoising and a Convolutional Neural Network (2024)
Collaboration Network
Top Collaborators
Joon Yoo
Gachon University (KR)
13 shared publications
- A comprehensive analysis of recent advancements in cancer detection using machine learning and deep learning models for improved diagnostics
- Comparative analysis of machine learning and deep learning models for improved cancer detection: A comprehensive review of recent advancements in diagnostic techniques
- Advancements in traditional machine learning techniques for detection and diagnosis of fatal cancer types: Comprehensive review of biomedical imaging datasets
- Two-headed UNetEfficientNets for parallel execution of segmentation and classification of brain tumors: incorporating postprocessing techniques with connected component labelling
- GAN-SkipNet: A Solution for Data Imbalance in Cardiac Arrhythmia Detection Using Electrocardiogram Signals from a Benchmark Dataset
Showing 5 of 13 shared publications
Kalyan Chatterjee
Indian Institute of Technology Dhanbad (IN)
7 shared publications
- Hybrid CNN-LSTM deep learning model and ensemble technique for automatic detection of myocardial infarction using big ECG data
- 2D MRI image analysis and brain tumor detection using deep learning CNN model LeU-Net
- Automatic and accurate abnormality detection from brain MR images using a novel hybrid UnetResNext-50 deep CNN model
- The prediction of cardiac abnormality and enhancement in minority class accuracy from imbalanced ECG signals using modified deep neural network models
- Myocardial Infarction Detection Using Deep Learning and Ensemble Technique from ECG Signals
Showing 5 of 7 shared publications
Saurabh Agarwal
Yeungnam University (KR)
7 shared publications
- Radar-Based Target Tracking Using Deep Learning Approaches with Unscented Kalman Filter
- LightweightUNet: Multimodal Deep Learning with GAN-Augmented Imaging Data for Efficient Breast Cancer Detection
- Advanced Noise-Resistant Electrocardiography Classification Using Hybrid Wavelet-Median Denoising and a Convolutional Neural Network
- The Improved Network Intrusion Detection Techniques Using the Feature Engineering Approach with Boosting Classifiers
- SwinConvNeXt: a fused deep learning architecture for Real-time garbage image classification
Showing 5 of 7 shared publications
Serhii Dashkevych
Vistula University (PL)
6 shared publications
- The prediction of cardiac abnormality and enhancement in minority class accuracy from imbalanced ECG signals using modified deep neural network models
- Advancements in traditional machine learning techniques for detection and diagnosis of fatal cancer types: Comprehensive review of biomedical imaging datasets
- Two-headed UNetEfficientNets for parallel execution of segmentation and classification of brain tumors: incorporating postprocessing techniques with connected component labelling
- GAN-SkipNet: A Solution for Data Imbalance in Cardiac Arrhythmia Detection Using Electrocardiogram Signals from a Benchmark Dataset
- Next-Generation Diagnostics: The Impact of Synthetic Data Generation on the Detection of Breast Cancer from Ultrasound Imaging
Showing 5 of 6 shared publications
Aditya Pal
Dongguk University (KR)
5 shared publications
- Advanced Noise-Resistant Electrocardiography Classification Using Hybrid Wavelet-Median Denoising and a Convolutional Neural Network
- Advanced Segmentation of Gastrointestinal (GI) Cancer Disease Using a Novel U-MaskNet Model
- ViT-DCNN: Vision Transformer with Deformable CNN Model for Lung and Colon Cancer Detection
- Transformative impacts of AI and the IoT on healthcare delivery
- Optimizing Financial Planning Through Advanced Machine Learning Techniques
Saule Amanzholova
International Information Technologies University (KZ)
4 shared publications
- IoT-based real-time monitoring and control system for tomato cultivation
- Revolutionizing Skin Cancer Detection: A Comprehensive Review of Deep Learning Methods
- Utilizing Smartwatches and Deep Learning Models for Enhanced Avalanche Victim Identification, Localization, and Efficient Recovery Strategies: An In-depth Study
- Transformative impacts of AI and the IoT on healthcare delivery
B. Omkar Lakshmi Jagan
Indian Institute of Management Visakhapatnam (IN)
4 shared publications
- Radar-Based Target Tracking Using Deep Learning Approaches with Unscented Kalman Filter
- SwinConvNeXt: a fused deep learning architecture for Real-time garbage image classification
- Deep Learning for Leukemia Classification: Performance Analysis and Challenges Across Multiple Architectures
- Vehicle tracking and classification for intelligent transportation systems using YOLOv5 and modified deep SORT with HRNN
Neha Agarwal
Yeungnam University (KR)
4 shared publications
- LightweightUNet: Multimodal Deep Learning with GAN-Augmented Imaging Data for Efficient Breast Cancer Detection
- Advanced Noise-Resistant Electrocardiography Classification Using Hybrid Wavelet-Median Denoising and a Convolutional Neural Network
- SwinConvNeXt: a fused deep learning architecture for Real-time garbage image classification
- Vehicle tracking and classification for intelligent transportation systems using YOLOv5 and modified deep SORT with HRNN
Syed Atif Moqurrab
International Information Technologies University (KZ)
3 shared publications
- Advancements in traditional machine learning techniques for detection and diagnosis of fatal cancer types: Comprehensive review of biomedical imaging datasets
- HRIDM: Hybrid Residual/Inception-Based Deeper Model for Arrhythmia Detection from Large Sets of 12-Lead ECG Recordings
- Transformative impacts of AI and the IoT on healthcare delivery
Abdul Razaque
Ohio Northern University
3 shared publications
In database
- Comparative analysis of machine learning and deep learning models for improved cancer detection: A comprehensive review of recent advancements in diagnostic techniques
- Advanced Segmentation of Gastrointestinal (GI) Cancer Disease Using a Novel U-MaskNet Model
- A depth analysis of recent innovations in non-invasive techniques using artificial intelligence approach for cancer prediction
Deepak Gupta
2 shared publications
- Agri-Bot: IoT Based Unmanned Smart Vehicle for Multiple Agriculture Operation
- Tumor Detection from Brain Magnetic Resonance Images Using MRDWTA-RBFNNC
Praween Srivastava
2 shared publications
- Myocardial Infarction Detection Using Deep Learning and Ensemble Technique from ECG Signals
- Tumor Detection from Brain Magnetic Resonance Images Using MRDWTA-RBFNNC
Minakshi Prasad
2 shared publications
- Imaging Techniques in Veterinary Disease Diagnosis
- Imaging Techniques in Veterinary Disease Diagnosis
Barnini Goswami
2 shared publications
- COVID-19 TravelCover: Post-Lockdown Smart Transportation Management System
- Intelligent Post-Lockdown Management System for Public Transportation
Shreya Majumdar
2 shared publications
- COVID-19 TravelCover: Post-Lockdown Smart Transportation Management System
- Intelligent Post-Lockdown Management System for Public Transportation
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