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Automatic detection of olive grove planting systems using Deep Learning algorithms

https://doi.org/10.2139/ssrn.6183764
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1 of the 23 references listed on this page is in the Retraction Watch database as retracted (export 2026-10-28): 10.1016/j.heliyon.2023.e19253 (notice 2026-01-22).

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s11119-020-09777-5openalex-snapshot
Semantic segmentation of citrus-orchard using deep neural networks and multispectral UAV-based imagery
inferredcites →https://doi.org/10.1016/j.aiia.2024.05.001openalex-snapshot
Hazelnut mapping detection system using optical and radar remote sensing: Benchmarking machine learning algorithms
inferredcites →https://doi.org/10.1016/j.atech.2022.100103openalex-snapshot
Trends in Remote Sensing Technologies in Olive Cultivation
inferredcites →https://doi.org/10.1016/j.baae.2023.04.005openalex-snapshot
Olive grove intensification negatively affects wintering bird communities in central Spain
inferredcites →https://doi.org/10.1016/j.ecoinf.2023.102217openalex-snapshot
A review of deep learning techniques used in agriculture
inferredcites →https://doi.org/10.1016/j.gltp.2022.04.020openalex-snapshot
A review: Data pre-processing and data augmentation techniques
inferredcites →https://doi.org/10.1016/j.heliyon.2023.e19253openalex-snapshot
RETRACTED: The effect of image resolution on convolutional neural networks in breast ultrasound
inferredcites →https://doi.org/10.1016/j.isprsjprs.2019.04.015openalex-snapshot
Deep learning in remote sensing applications: A meta-analysis and review
inferredcites →https://doi.org/10.1016/j.iswcr.2021.01.003openalex-snapshot
In-depth analysis of soil management and farmers’ perceptions of related risks in two olive grove areas in southern Spain
inferredcites →https://doi.org/10.1016/j.procs.2023.01.274openalex-snapshot
Exploratory approach for automatic detection of vine rows in terrace vineyards
inferredcites →https://doi.org/10.1016/j.scib.2019.03.002openalex-snapshot
Stable classification with limited sample: transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017
inferredcites →https://doi.org/10.1016/j.scitotenv.2021.149212openalex-snapshot
Environmental challenges of intensive woody crops: The case of super high-density olive groves
inferredcites →https://doi.org/10.1080/01431161.2018.1433343openalex-snapshot
Implementation of machine-learning classification in remote sensing: an applied review
inferredcites →https://doi.org/10.1094/phyto-08-18-0288-ropenalex-snapshot
Using Deep Learning for Image-Based Potato Tuber Disease Detection
inferredcites →https://doi.org/10.1109/access.2018.2884199openalex-snapshot
Remote Sensing: An Automated Methodology for Olive Tree Detection and Counting in Satellite Images
inferredcites →https://doi.org/10.1109/lgrs.2017.2681128openalex-snapshot
Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data
inferredcites →https://doi.org/10.1109/tgrs.2020.3024852openalex-snapshot
Target Detection Through Tree-Structured Encoding for Hyperspectral Images
inferredcites →https://doi.org/10.14358/pers.76.3.289openalex-snapshot
Accuracy Assessment Measures for Object-based Image Segmentation Goodness
inferredcites →https://doi.org/10.3389/fpls.2022.992700openalex-snapshot
The power of transfer learning in agricultural applications: AgriNet
inferredcites →https://doi.org/10.3390/agriengineering4040056openalex-snapshot
A VGG-19 Model with Transfer Learning and Image Segmentation for Classification of Tomato Leaf Disease
inferredcites →https://doi.org/10.3390/diagnostics11122183openalex-snapshot
Impact of Image Resolution on Deep Learning Performance in Endoscopy Image Classification: An Experimental Study Using a Large Dataset of Endoscopic Images
inferredcites →https://doi.org/10.3390/rs14235951openalex-snapshot
The Role of Remote Sensing in Olive Growing Farm Management: A Research Outlook from 2000 to the Present in the Framework of Precision Agriculture Applications
inferredcites →https://doi.org/10.3390/s19245558openalex-snapshot
Citrus Tree Segmentation from UAV Images Based on Monocular Machine Vision in a Natural Orchard Environment
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