Abstract Our general interest is in global trade loss from livestock pathogens, specifically exports. We adopt a causal inference approach that considers animal disease outbreaks over time as non‐staggered binary treatments with the potential for switching in (infection) and out of treatment (recovery) within the sample period. The outcome evolution of
Mohammad Maksudur Rahman +1 more
wiley +1 more source
Attention-PestNet: hierarchical scaled dot-product attention for insect pest detection. [PDF]
Doan VT, Le HT, Pham TTT, Dai HJ.
europepmc +1 more source
Maize-YOLO: A New High-Precision and Real-Time Method for Maize Pest Detection. [PDF]
Yang S +8 more
europepmc +1 more source
Abstract Crop insurance is undoubtedly an extremely valuable element in protecting agricultural businesses, but in many cases standard indemnity‐based products have had very low uptake due to high transaction costs elevating premiums to unaffordable levels.
Amogh Prakasha Kumar +2 more
wiley +1 more source
PalmNeXt: a ConvNeXt-based deep learning model for pest detection in date palm leaves. [PDF]
Ashraf M, Aslam MZ, Saeed N, Hussain SJ.
europepmc +1 more source
A new deep learning-based technique for rice pest detection using remote sensing. [PDF]
Hassan SI +3 more
europepmc +1 more source
An Efficient Pest Detection Framework with a Medium-Scale Benchmark to Increase the Agricultural Productivity. [PDF]
Aladhadh S +5 more
europepmc +1 more source
CropCLR-Wheat: A Label-Efficient Contrastive Learning Architecture for Lightweight Wheat Pest Detection. [PDF]
Wang Y +6 more
europepmc +1 more source
Automatic Crop Pest Detection Oriented Multiscale Feature Fusion Approach. [PDF]
Dong S +6 more
europepmc +1 more source
YOLO-DCPG: a lightweight architecture with dual-channel pooling gated attention for intensive small-target agricultural pest detection. [PDF]
Liu J, Yu E, Li Y, Zhao Y, Mao B.
europepmc +1 more source

