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Potato crop stress identification in aerial images using deep learning‐based object detection

https://doi.org/10.1002/agj2.20841
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What this work says

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

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Advanced methods of plant disease detection. A review
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Deep localization model for intra-row crop detection in paddy field
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Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives
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Early Disease Detection in Wheat Fields using Spectral Reflectance
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Deep Residual Learning for Image Recognition
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Feature Pyramid Networks for Object Detection
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YOLO9000: Better, Faster, Stronger
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Unsupervised Convolutional Autoencoder-Based Feature Learning for Automatic Detection of Plant Diseases
inferredcites →https://doi.org/10.1109/iccv.2017.322openalex-snapshot
Mask R-CNN
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inferredcites →https://doi.org/10.1109/ieecon.2018.8712217openalex-snapshot
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inferredcites →https://doi.org/10.1109/jstars.2014.2329330openalex-snapshot
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inferredcites →https://doi.org/10.1109/lra.2017.2774979openalex-snapshot
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inferredcites →https://doi.org/10.1109/mitp.2020.2986103openalex-snapshot
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inferredcites →https://doi.org/10.1109/tpami.2018.2858826openalex-snapshot
Focal Loss for Dense Object Detection
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inferredcites →https://doi.org/10.1155/2016/3289801openalex-snapshot
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inferredcites →https://doi.org/10.3389/fpls.2016.01419openalex-snapshot
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inferredcites →https://doi.org/10.3390/s16081222openalex-snapshot
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inferredcites →https://doi.org/10.3390/sym10010011openalex-snapshot
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inferredcites →https://doi.org/10.4236/ars.2018.72006openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.1709.03329openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.1811.08661openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.1912.13199openalex-snapshot
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inferredcites →https://doi.org/10.5220/0007383900002108openalex-snapshot
Plant Diseases Recognition from Digital Images using Multichannel Convolutional Neural Networks

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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