Dr. Sandeep Singh Sengar

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Lecturer

Cardiff University

United Kingdom

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About

Dr. Sandeep Singh Sengar is a Lecturer at Cardiff Metropolitan University in the UK. His research areas include generative artificial intelligence, machine learning applications in abnormal activity recognition, and deep learning models for autism spectrum disorder classification. Additionally, he investigates computer vision technologies and their application in digital document processing, as well as trust-aware routing mechanisms in IoT-enabled sensor networks.

Recent Grants

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Erasmus+ International Credit Mobility 2020-2023 project.

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Global Academies Interdisciplinary Research and Innovation Development Fund

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Articles (12)

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2020

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2020

Collaborators (4)

Fiona Carroll

Senior Lecturer

Cardiff University

UNITED KINGDOM

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Mathias Perslev

Københavns Universitet

DENMARK

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henrik gudbergsen

Københavns Universitet

DENMARK

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Erik Bjørnager Dam

Københavns Universitet

DENMARK

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Dr. Sandeep Singh Sengar

Research Interests

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About

Recent Grants

Articles (12)

Generative artificial intelligence

Human Abnormal Activity Recognition from Video Using Motion Tracking

Multi‐planar 3D knee MRI segmentation via UNet inspired architectures

Age-and Severity- Specific Deep Learning Models for Autism Spectrum Disorder Classification Using Functional Connectivity Measures

Machine-Learning-Based Spam Mail Detector

Design and Development of Artificial Intelligence Knowledge Processing System for Optimizing Security of Software System

Computer Vision Based Automatic Margin Computation Model for Digital Document Images

Exploration of Despair Eccentricities Based on Scale Metrics with Feature Sampling Using a Deep Learning Algorithm

Trust-Aware Routing Mechanism through an Edge Node for IoT-Enabled Sensor Networks

Community detection in complex networks using stacked autoencoders and crow search algorithm

Motion segmentation-based surveillance video compression using adaptive particle swarm optimization

Moving object detection using statistical background subtraction in wavelet compressed domain

Collaborators (4)

Fiona Carroll

Mathias Perslev

henrik gudbergsen

Erik Bjørnager Dam

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