Indrajeet Gupta
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View article: ClearNet: auto-encoder based denoising model for endoscopy images
ClearNet: auto-encoder based denoising model for endoscopy images Open
Gastrointestinal (GI) endoscopy images play a crucial role in the detection and diagnosis of diseases within the digestive tract. However, the development of effective computer vision models for automated analysis and denoising of endoscop…
View article: A Novel Ensemble Empirical Decomposition and Time–Frequency Analysis Approach for Vibroarthrographic Signal Processing
A Novel Ensemble Empirical Decomposition and Time–Frequency Analysis Approach for Vibroarthrographic Signal Processing Open
Signal processing techniques play a critical role in addressing real-world applications across domains such as sensor analysis, defence, and clinical and biomedical fields. Within healthcare, computer-aided diagnostic (CAD) systems have be…
View article: Hybrid deep learning model for density and growth rate estimation on weed image dataset
Hybrid deep learning model for density and growth rate estimation on weed image dataset Open
View article: Enhancing Brain Tumor Segmentation using Berkeley Wavelet Transformation and Improved SVM
Enhancing Brain Tumor Segmentation using Berkeley Wavelet Transformation and Improved SVM Open
Aims This research gives insight into the various machine learning models like enhanced Support Vector Machines (SVM), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Artificial Neural Networks (ANN) in brain tumo…
View article: Deep Learning-based Staging of Throat Cancer for Enhancing Diagnostic Accuracy Through Multimodal Data Integration
Deep Learning-based Staging of Throat Cancer for Enhancing Diagnostic Accuracy Through Multimodal Data Integration Open
Aim This study strives to develop deep learning models with respect to the staging of throat cancer through CT image analysis linked with medical records. Using 650 CT scans, the current research combines the convolutional neural networks …
View article: Minimal sourced and lightweight federated transfer learning models for skin cancer detection
Minimal sourced and lightweight federated transfer learning models for skin cancer detection Open
One of the most fatal diseases that affect people is skin cancer. Because nevus and melanoma lesions are so similar and there is a high likelihood of false negative diagnoses challenges in hospitals. The aim of this paper is to propose and…
View article: Preventing Data Leakage and Electoral Fraud through Blockchain-Based Anomaly Detection
Preventing Data Leakage and Electoral Fraud through Blockchain-Based Anomaly Detection Open
View article: Zero-Day Insider Threat Detection via Attention-Based Neural Networks on Synthetic Access Logs
Zero-Day Insider Threat Detection via Attention-Based Neural Networks on Synthetic Access Logs Open
View article: Anomaly Detection through Behavior Analysis: A Deep Learning Approach for Identifying Unusual User Activities
Anomaly Detection through Behavior Analysis: A Deep Learning Approach for Identifying Unusual User Activities Open
View article: Enhanced neurological anomaly detection in MRI images using deep convolutional neural networks
Enhanced neurological anomaly detection in MRI images using deep convolutional neural networks Open
Introduction Neurodegenerative diseases, including Parkinson’s, Alzheimer’s, and epilepsy, pose significant diagnostic and treatment challenges due to their complexity and the gradual degeneration of central nervous system structures. This…
View article: A New-fangled Classification Algorithm for Medical Heart Diseases Analysis using Wavelet Transforms
A New-fangled Classification Algorithm for Medical Heart Diseases Analysis using Wavelet Transforms Open
Background In this article, the Mixed Mode Database Miner (MMDBM) algorithm is introduced for the classification of data. This algorithm depends on the decision tree classifier, which handles the numerical and categorical attributes. For t…
View article: Integrating Radial Basis Networks and Deep Learning for Transportation
Integrating Radial Basis Networks and Deep Learning for Transportation Open
Introduction This research focuses on the concept of integrating Radial Basis Function Networks with deep learning models to solve robust regression tasks in both transportation and logistics. Methods It examines such combined models as RN…
View article: Utilizing Multi-layer Perceptron for Esophageal Cancer Classification Through Machine Learning Methods
Utilizing Multi-layer Perceptron for Esophageal Cancer Classification Through Machine Learning Methods Open
Aims This research paper aims to check the effectiveness of a variety of machine learning models in classifying esophageal cancer through MRI scans. The current study encompasses Convolutional Neural Network (CNN), K-Nearest Neighbor (KNN)…
View article: Enhancing Large-Diameter Tunnel Construction Safety with Robust Optimization and Machine Learning Integrated into BIM
Enhancing Large-Diameter Tunnel Construction Safety with Robust Optimization and Machine Learning Integrated into BIM Open
Aim This study aims to enhance safety in large diameter tunnel construction by integrating robust optimization and machine learning (ML) techniques with Building Information Modeling (BIM). By acquiring and preprocessing various datasets, …
View article: Automatic Kidney Stone Detection System using Guided Bilateral Feature Detector for CT Images
Automatic Kidney Stone Detection System using Guided Bilateral Feature Detector for CT Images Open
Background Kidney stones, common urological diseases worldwide, are formed from hard urine minerals in the kidneys. Early detection is essential to prevent kidney damage and manage recurring stones. CT imaging has made significant progress…
View article: Advancing Tunnel Construction Reliability with Automated Artificial Intelligence under Geotechnical and Aleatoric Uncertainties
Advancing Tunnel Construction Reliability with Automated Artificial Intelligence under Geotechnical and Aleatoric Uncertainties Open
Aims This research seeks to improve the reliability and sustainability of tunnel construction by employing automated AI techniques to manage geotechnical and aleatoric uncertainties. It utilizes machine learning models, including Gradient …
View article: Deep Learning and MRI Biomarkers for Precise Lung Cancer Cell Detection and Diagnosis
Deep Learning and MRI Biomarkers for Precise Lung Cancer Cell Detection and Diagnosis Open
Aim This research work aimed to combine different AI methods to create a modular diagnosis system for lung cancer, including Convolutional Neural Network (CNN), K-Nearest Neighbors (KNN), VGG16, and Recurrent Neural Network (RNN) on MRI bi…
View article: Radiotherapy in cervical cancer
Radiotherapy in cervical cancer Open
Radiotherapy plays a significant role in the management of cervix cancer. In recent decades, there have been several advancements in radiation therapy treatment techniques. Moving from conventional two-dimensional techniques to advanced te…
View article: Energy Optimized Workflow Scheduling in IaaS Cloud: A Flower Pollination based Approach
Energy Optimized Workflow Scheduling in IaaS Cloud: A Flower Pollination based Approach Open
The energy consumption of cloud data centers is a critical concern that could affect both the environment and the availability of energy resources. For this, the global community and industries are taking measures to address this issue tha…
View article: CloudConsumerism: A Consumer-Centric Ranking Model for Efficient Service Mapping in Cloud
CloudConsumerism: A Consumer-Centric Ranking Model for Efficient Service Mapping in Cloud Open
In cloud, service providers and consumers are primary stakeholders that maintain a business liaison. Cloud service providers (CSPs) offer the services, and consumer uses the services on a payment basis. From a business perspective, the sel…
View article: Energy‐Efficient Scientific Workflow Scheduling Algorithm in Cloud Environment
Energy‐Efficient Scientific Workflow Scheduling Algorithm in Cloud Environment Open
Scheduling extensive scientific applications that are deadline‐aware (usually referred to as workflow) is a difficult task. This research provides a virtual machine (VM) placement and scheduling approach for effectively scheduling process …
View article: Allocation-aware Task Scheduling for Heterogeneous Multi-cloud Systems
Allocation-aware Task Scheduling for Heterogeneous Multi-cloud Systems Open
Cloud computing is one of the growing technology usage for the day-to-day business operations in today's IT industry. The diverse features of cloud such as on-demand self-service, quality of service, pay-per-usage pricing, virtualization a…