Indrajit De

A Secure Energy-Aware IoT Solution for Remote Health Monitoring and Patient Localization

Manab Kumar Das, Proshanta Sarkar, Soham Goswami, Kaustav Nandy et autres

An Internet of Things (IoT) based healthcare system is extremely beneficial for continuous patient observation beyond hospital settings. The patients recovering from surgery are helpful with this cutting-edge technology. In recent days most of the existing approaches primarily focus on real-time health …

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Anomaly Detection in Network Traffic using Quantized MLP Autoencoder on CICIDS2017 Dataset

Shivyansh Rai, Indrajit Banerjee, Indrajit De

Anomaly detection plays a critical role in network security to identify unusual behavior or attacks in data traffic. As networks grow in complexity and size, deep learning models like autoencoders have gained popularity due to their unsupervised detection capability. However, most of …

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Aegis: FTL Framework with Differential Privacy for Network-Based IDS

Arjun Ghoshal, Rajdeep Das, Arpita Kundu, Indrajit De et autres

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IoT Enable Secured Indoor Environment Monitoring System for Patient Care

Manab Kumar Das, Priti Deb, Indrajit De

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AI-Powered Fraud Detection in Real-Time Financial Transactions

Vishnu Ravi, Vineet Kumar Srivastava, Maninder Singh, Ravi Kumar Burila et autres

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Explainable AI (XAI) for Credit Scoring and Loan Approvals

Vishnu Ravi, Vineet Kumar Srivastava, Maninder Singh, Ravi Kumar Burila et autres

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Generative AI for Financial Forecasting and Portfolio Optimization

Vishnu Ravi, Vineet Kumar Srivastava, Maninder Pal Singh, Chippagiri Srinivas et autres

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iDetect: An Automated Anomaly Detection System for Industrial Internet of Things Data

Pradeep Kumar, Rajdeep Das, Arjun Ghoshal, Riya Layek et autres

Enhancing white blood cell classification via fixed segmentation and learnable blending

Roshan Rateria, Subhajit Adhikari, Indrajit De

Accurate and timely classification of white blood cells (WBCs) is crucial for diagnosing a myriad of hematological disorders, including leukemia. While deep learning models, particularly Convolutional Neural Networks (CNNs), have shown promise in automating this task from microscopic blood smear images, their …

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Integrating Bayesian methods with neural networks for enhanced climatology models

Charu Awasthi, Indrajit De, Deepak Chaudhary, Divya Sharma et autres

Abstract The increasing complexity of climate systems and the need for accurate predictive models necessitate innovative approaches to enhance climatology models. This manuscript investigates the coupling of these two techniques in an attempt to leverage the individual strengths. Bayesian approaches offer a …

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Innovating Network Security: Federated Transfer Learning for Intrusion Detection

Rajdeep Das, A. Ghosal, Arpita Kundu, Indrajit De et autres

Due to the dynamic nature of threats in cyberspace, there is need for sophisticated IDS that can offer online and adaptant security solutions to various network structures. For this purpose, this paper suggests a new approach that uses federated transfer learning to …

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SignCraft: Khasi Sign Language Recognition Application

Madhurima Mukherjee, Riya Layek, Lincolin Amory Ranee, Indrajit De et autres

SignCraft is an innovative Smartphone application developed to assist the Khasi deaf community in communicating effectively through the recognition of signs in Khasi Sign Language (KSL). The app utilizes hi-tech features like computer vision and deep learning to identify the gestures. It …

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