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Olive Disease Classification Based on Vision Transformer and CNN Models

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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-030-58452-8_13openalex-snapshot
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Plants Disease Identification and Classification Through Leaf Images: A Survey
inferredcites →https://doi.org/10.1007/s12652-020-02505-xopenalex-snapshot
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inferredcites →https://doi.org/10.1016/j.atech.2022.100048openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.compag.2018.01.009openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.compag.2019.105146openalex-snapshot
Research on deep learning in apple leaf disease recognition
inferredcites →https://doi.org/10.1016/j.compag.2021.106252openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.compeleceng.2022.107716openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.inpa.2019.10.003openalex-snapshot
Automatic grape leaf diseases identification via UnitedModel based on multiple convolutional neural networks
inferredcites →https://doi.org/10.1016/j.phpro.2012.03.133openalex-snapshot
An Improved Median Filtering Algorithm for Image Noise Reduction
inferredcites →https://doi.org/10.1016/j.procs.2020.03.285openalex-snapshot
Olive Spot Disease Detection and Classification using Analysis of Leaf Image Textures
inferredcites →https://doi.org/10.1016/j.proeng.2014.12.356openalex-snapshot
A Study on Development of Optimal Noise Filter Algorithm for Laser Vision System in GMA Welding
inferredcites →https://doi.org/10.1109/access.2019.2947160openalex-snapshot
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inferredcites →https://doi.org/10.1109/access.2021.3069646openalex-snapshot
Plant Disease Detection and Classification by Deep Learning—A Review
inferredcites →https://doi.org/10.1109/cdma47397.2020.00025openalex-snapshot
Deep Convolutional Neural Network Based Image Spam Classification
inferredcites →https://doi.org/10.1109/csase48920.2020.9142097openalex-snapshot
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ImageNet classification with deep convolutional neural networks
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inferredcites →https://doi.org/10.1155/2022/6504616openalex-snapshot
A Hybrid Model for Leaf Diseases Classification Based on the Modified Deep Transfer Learning and Ensemble Approach for Agricultural AIoT-Based Monitoring
inferredcites →https://doi.org/10.1155/2022/8531213openalex-snapshot
Optimal Deep Learning Model for Olive Disease Diagnosis Based on an Adaptive Genetic Algorithm
inferredcites →https://doi.org/10.1155/2022/8950243openalex-snapshot
Tuberculosis Disease Diagnosis Based on an Optimized Machine Learning Model
inferredcites →https://doi.org/10.1155/2022/9211700openalex-snapshot
Design and Evaluation of a Hybrid Technique for Detecting Sunflower Leaf Disease Using Deep Learning Approach
inferredcites →https://doi.org/10.1186/s40537-019-0197-0openalex-snapshot
A survey on Image Data Augmentation for Deep Learning
inferredcites →https://doi.org/10.1186/s40537-021-00492-0openalex-snapshot
Text Data Augmentation for Deep Learning
inferredcites →https://doi.org/10.14569/ijacsa.2019.0100863openalex-snapshot
An Efficient Deep Learning Model for Olive Diseases Detection
inferredcites →https://doi.org/10.2139/ssrn.4003105openalex-snapshot
Crops Yield Prediction Based on Machine Learning Models: Case of West African Countries
inferredcites →https://doi.org/10.3389/fpls.2016.01419openalex-snapshot
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Adam: A Method for Stochastic Optimization

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inferred← citeshttps://doi.org/10.1002/agj2.70035openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-47724-9_44openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-49361-4_2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-97825-8_41openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-95-4161-4_26openalex-snapshot
MaizeViT: Detection and Classification of Maize Leaf Diseases Using Convolutional Networks and Vision Transformers
inferred← citeshttps://doi.org/10.1007/978-981-96-0644-3_43openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-97-1923-5_18openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-97-4228-8_5openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-99-7711-6_41openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s00217-023-04386-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10341-026-01774-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10462-024-11100-xopenalex-snapshot
Deep learning and computer vision in plant disease detection: a comprehensive review of techniques, models, and trends in precision agriculture
inferred← citeshttps://doi.org/10.1007/s12161-026-02985-1openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s41348-023-00807-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s41348-024-00934-wopenalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.aej.2023.03.081openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.aej.2023.07.037openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.aej.2023.10.057openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.array.2023.100286openalex-snapshot
On field disease detection in olive tree with vision systems
inferred← citeshttps://doi.org/10.1016/j.atech.2025.100813openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.compag.2023.107862openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.ecoinf.2023.102276openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.engappai.2025.111320openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.engappai.2025.113470openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.eswa.2024.124113openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.heliyon.2024.e36361openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.heliyon.2024.e41480openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.indcrop.2026.122971openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.iot.2022.100650openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.iswa.2025.200490openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jfca.2024.106337openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jfca.2026.109106openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.neucom.2024.128608openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.rsase.2026.101971openalex-snapshot
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inferred← citeshttps://doi.org/10.1038/s41598-025-31918-xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1038/s44334-025-00025-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1063/5.0343442openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2024.3352745openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2024.3485479openalex-snapshot
FMMix: A Novel Augmentation Strategy for Enhancing Feature Diversity to Boost Model Generalization for Image Data
inferred← citeshttps://doi.org/10.1109/access.2025.3563160openalex-snapshot
BorB: A Novel Image Segmentation Technique for Improving Plant Disease Classification With Deep Learning Models
inferred← citeshttps://doi.org/10.1109/access.2025.3609540openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/atigb66719.2025.11142197openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/esic60604.2024.10481592openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icabcd59051.2023.10220517openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icar58858.2023.10436499openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icccnt56998.2023.10307591openalex-snapshot
Retracted: A Comparison of Two Transformers in the Study of Plant Disease Classification
inferred← citeshttps://doi.org/10.1109/icces57224.2023.10192615openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/iceca63461.2024.10800909openalex-snapshot
A Deep-Siamese CNN-based Approach for Identifying Mycosphaerella Coffeeicola Disease in Coffee Foliage
inferred← citeshttps://doi.org/10.1109/iceee69936.2026.11598274openalex-snapshot
A Hybrid CNN-Transformer Approach for Automated Olive Leaf Disease Classification
inferred← citeshttps://doi.org/10.1109/icoecit68303.2026.11497373openalex-snapshot
Revolutionizing Guava Leaf Disease Detection-Unleashing the Power of Vision Transformers over CNNs
inferred← citeshttps://doi.org/10.1109/icosec67334.2025.11459492openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icrteect67512.2025.11448728openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/ict62760.2024.10606117openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/incet61516.2024.10593619openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/inocon60754.2024.10511970openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/les.2024.3370634openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/ojcs.2024.3419027openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/raai56146.2022.10093001openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tce.2025.3582267openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/jph.13438openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3757232.3757240openalex-snapshot
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inferred← citeshttps://doi.org/10.11591/ijece.v14i1.pp891-903openalex-snapshot
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inferred← citeshttps://doi.org/10.1177/10943420251408184openalex-snapshot
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inferred← citeshttps://doi.org/10.1186/s13007-025-01423-3openalex-snapshot
VCPC: virtual contrastive constraint and prototype calibration for few-shot class-incremental plant disease classification
inferred← citeshttps://doi.org/10.14569/ijacsa.2023.0140494openalex-snapshot
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inferred← citeshttps://doi.org/10.15439/2023f4794openalex-snapshot
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inferred← citeshttps://doi.org/10.2139/ssrn.5346178openalex-snapshot
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inferred← citeshttps://doi.org/10.24214/jecet.b.12.4.16175openalex-snapshot
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inferred← citeshttps://doi.org/10.32604/cmc.2024.047604openalex-snapshot
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inferred← citeshttps://doi.org/10.32628/ijsrset2512160openalex-snapshot
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inferred← citeshttps://doi.org/10.33411/ijist/1667openalex-snapshot
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inferred← citeshttps://doi.org/10.33411/ijist/202461237248openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fdata.2025.1609124openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fpls.2022.1095547openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fpls.2025.1676798openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fpls.2026.1736123openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/agriculture13030737openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/agriculture16050626openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/agriengineering5040139openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/agronomy15010077openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/agronomy16111057openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/app142411771openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/computers12080151openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/inventions8050129openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/jimaging11100326openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/s26113456openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/su151813723openalex-snapshot
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inferred← citeshttps://doi.org/10.34133/plantphenomics.0159openalex-snapshot
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inferred← citeshttps://doi.org/10.4018/979-8-3693-8019-2.ch005openalex-snapshot
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inferred← citeshttps://doi.org/10.4236/ijcns.2026.193003openalex-snapshot
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inferred← citeshttps://doi.org/10.47495/okufbed.1392386openalex-snapshot
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inferred← citeshttps://doi.org/10.48084/etasr.15939openalex-snapshot
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inferred← citeshttps://doi.org/10.55251/jmbfs.10588openalex-snapshot
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inferred← citeshttps://doi.org/10.7717/peerj-cs.3544openalex-snapshot
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