Alex Shenfield

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Associate Professor in Machine Learning

Sheffield Hallam University

United Kingdom

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About

Alex Shenfield is an Associate Professor in Machine Learning at Sheffield Hallam University, UK. His research encompasses various areas including AI applications in healthcare, food safety, and privacy in smart home systems. Recent publications highlight innovative approaches in machine learning, such as surrogate models in food manufacturing and real-time detection methods in healthcare contexts. His work also addresses critical issues related to security and ethical considerations in technology deployment.

Recent Grants

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Next generation rice processing

Open Date: 2019-03-31

Close Date: 2021-03-30

Articles (15)

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Collaborators (8)

Olusogo Popoola

Associate Lecturer

Sheffield Hallam University

UNITED KINGDOM

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Alex Brandsen

Royal Netherlands Academy of Arts & Sciences (KNAW)

NETHERLANDS

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Ali Sadeghi-Naini

Assistant Professor

York University

CANADA

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Giuseppe ALTIERI

Associate Research Professor

Università degli Studi di Napoli Federico II

ITALY

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Urban Emmenegger

University of Toronto

CANADA

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WILLIAM T TRAN

Assistant Professor

University of Toronto

CANADA

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Marcos Aurelio Rodrigues

Professor of Computer Science

Sheffield Hallam University

UNITED KINGDOM

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Charmaine Childs

Sheffield Hallam University

UNITED KINGDOM

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Alex Shenfield

Research Interests

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About

Recent Grants

Articles (15)

AI-Based Surrogate Models for the Food and Drink Manufacturing Industry: A Comprehensive Review

Real-Time Rice Milling Morphology Detection Using Hybrid Framework of YOLOv8 Instance Segmentation and Oriented Bounding Boxes

C3-VULMAP: A Dataset for Privacy-Aware Vulnerability Detection in Healthcare Systems

An optimized hybrid encryption framework for smart home healthcare: Ensuring data confidentiality and security

A critical literature review of security and privacy in smart home healthcare schemes adopting IoT & blockchain: Problems, challenges and solutions

Hyperspectral Imaging Aiding Artificial Intelligence: A Reliable Approach for Food Qualification and Safety

Debating AI in Archaeology: applications, implications, and ethical considerations

Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning

Segmentation Agreement and AI-Based Feature Extraction of Cutaneous Infrared Images of the Obese Abdomen after Caesarean Section: Results from a Single Training Session

Assessment of Digital Pathology Imaging Biomarkers Associated with Breast Cancer Histologic Grade

A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks.

A Novel Deep Learning Model for the Detection and Identification of Rolling Element-Bearing Faults

Do Temporal Changes in Facial Expressions Help Identify Patients at Risk of Deterioration in Hospital Wards? A Post Hoc Analysis of the Visual Early Warning Score Study.

Accurate detection of sleep apnea with long short-term memory network based on RR interval signals

Validating the robustness of an internet of things based atrial fibrillation detection system

Collaborators (8)

Olusogo Popoola

Alex Brandsen

Ali Sadeghi-Naini

Giuseppe ALTIERI

Urban Emmenegger

WILLIAM T TRAN

Marcos Aurelio Rodrigues

Charmaine Childs

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