Dean Diepeveen

Orcid: 0000-0002-1535-8019

According to our database1, Dean Diepeveen authored at least 15 papers between 2007 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Deep Learning-based Depth Estimation Methods from Monocular Image and Videos: A Comprehensive Survey.
ACM Comput. Surv., December, 2024

LoRa-based outdoor localization and tracking using unsupervised symbolization.
Internet Things, April, 2024

LoRa localisation using single mobile gateway.
Comput. Commun., 2024

Early frost detection in wheat using machine learning from vertical temperature distributions.
Comput. Electron. Agric., 2024

Plant disease recognition in a low data scenario using few-shot learning.
Comput. Electron. Agric., 2024

Multi-task learning model for agricultural pest detection from crop-plant imagery: A Bayesian approach.
Comput. Electron. Agric., 2024

2023
Image patch-based deep learning approach for crop and weed recognition.
Ecol. Informatics, December, 2023

Machine learning-based LoRa localisation using multiple received signal features.
IET Wirel. Sens. Syst., August, 2023

Deep learning-based detection of aphid colonies on plants from a reconstructed <i>Brassica</i> image dataset.
Comput. Electron. Agric., February, 2023

2022
Machine learning-based detection of freezing events using infrared thermography.
Comput. Electron. Agric., 2022

2021
Weed Recognition using Deep Learning Techniques on Class-imbalanced Imagery.
CoRR, 2021

A survey of deep learning techniques for weed detection from images.
Comput. Electron. Agric., 2021

2010
An eAgriculture-Based Decision Support Framework for Information Dissemination.
Int. J. Hum. Cap. Inf. Technol. Prof., 2010

2009
Selecting Areas for Land Use Change in a Catchment.
Proceedings of the 4th Indian International Conference on Artificial Intelligence, 2009

2007
The application of data mining techniques to characterize agricultural soil profiles.
Proceedings of the Data Mining and Analytics 2007, 2007


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