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Laura Elena Raileanu

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Head of Health, Engineering and Economics (HEE) group

Haute école d'ingénierie et de gestion du canton de Vaud

Switzerland

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Professors in Switzerland Professors in Plant Biology Plant Biology professors in Switzerland

About

Laura Elena Raileanu is the Head of the Health, Engineering and Economics (HEE) group at Haute école d'ingénierie et de gestion du canton de Vaud, Switzerland. Her research focuses on the application of machine learning and IoT technologies in agriculture, particularly in the areas of plant electrophysiology and nutrient assessment. Recent articles include the development of intelligent advisory systems for fruit growth and innovative methods for detecting stress in crops.

Recent Grants

Grant: Open

Exploring Multidimensional Temporal Trajectories of Low Back Pain Progression and Remission

Open Date: 2024-06-01

Close Date: 2028-05-31

Grant: Close

Machine Learning Techniques to extract eye movements trajectories from MRI data (MREye-Track)

Open Date: 2024-05-01

Close Date: 2026-04-01

Grant: Close

Estimation des récoltes avec la détection de fruits sur les images et l’analyse intelligente de données (ERALD)

Open Date: 2024-05-01

Close Date: 2025-04-01

Grant: Close

Substitution 2023

Open Date: 2022-01-01

Close Date:

Grant: Close

Novel #fruit growers advisory system# using connected fruit dendrometer, micro-climate data and machine learning algorithms

Open Date: 2021-11-01

Close Date: 2023-11-01

Articles (14)

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2026

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2023

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2023

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2023

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2022

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Associate professor

University of Applied Sciences and Arts Western Switzerland (HES-SO)

SWITZERLAND

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Laura Elena Raileanu

Research Interests

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About

Recent Grants

Articles (14)

Reliability and convergent validity of smartphone-based discrete and continuous measures of spinal kinematics in asymptomatic individuals

Development of an AI-based interactive tool to support radiographer training in chest x-ray analysis

An intelligent IoT platform as an advisory system for fruit growth

Novel fruit growers’ advisory system using connected fruit dendrometer, micro-climate data and machine learning algorithms

Exploring Multidimensional Trajectories in Low Back Pain: Protocol for a Longitudinal Cohort Study

LSTM-Based Prediction of Apple Fruit Growth Using Past Diameter and Climatic Condition Data

Automated Identification of Eye Motion in Raw MRI Data Using Machine Learning

Advanced assessment of nutrient deficiencies in greenhouse with electrophysiological signals

Assessment of the universality of the electrophysiological signal acquired from tomatoes and eggplants

Plant electrophysiology for smart irrigation management of greenhouse

Detecting stress caused by nitrogen deficit using deep learning techniques applied on plant electrophysiological data

De la pratique fondée sur les preuves à l’amélioration de la qualité pour des soins de haute valeur centrés sur le patient

Identifying General Stress in Commercial Tomatoes Based on Machine Learning Applied to Plant Electrophysiology

Classification of Plant Electrophysiology Signals for Detection of Spider Mites Infestation in Tomatoes

Collaborators (5)

Cedric Camps

Fabien Dutoit

Stefan Schmid

Ricardo Teresa Ribeiro

Marco Mazza

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