Results 101 to 110 of about 824 (172)

LiSA-MobileNetV2: an extremely lightweight deep learning model with Swish activation and attention mechanism for accurate rice disease classification. [PDF]

Front Plant Sci
Xu Y, Li D, Li C, Yuan Z, Dai Z.
europepmc   +1 more source

RiceDetect-Net: a lightweight real-time detection framework for rice diseases. [PDF]

BMC Plant Biol
Yuan X, Xu Q, Wang T, Gao L, Zhao G, Jia L, Wang Y.   +6 more
europepmc   +1 more source

Begomoviral pre-coat protein boosts potato virus X in mixed infection through interfering with antiviral RNAi response. [PDF]

Virol J
Ghosh D, Malavika M, Rawat P, Chakraborty S.   +3 more
europepmc   +1 more source

Hybrid deep learning for smart paddy disease diagnosis using self supervised hierarchical reconstruction and attention based temporal analysis. [PDF]

Sci Rep
Thanuboddi N, Nelakuditi UR.
europepmc   +1 more source

Characterization of a novel psyllid-transmitted waikavirus in carrots. [PDF]

Virus Res, 2023
Shushan A, Luria N, Lachman O, Sela N, Laskar O, Belausov E, Smith E, Dombrovsky A.   +7 more
europepmc   +1 more source

Phylogenomics, population structure, and symbiont diversity refine the systematics of Southeast Asian rice leafhoppers (Hemiptera: Cicadellidae). [PDF]

J Insect Sci
Detcharoen M, Saksongmuang V, Nilsai A.
europepmc   +1 more source

Classification of rice plant diseases using efficient DenseNet121. [PDF]

Sci Rep
Ismail A, Hamdy W, Ibrahim AH, Awad WA.
europepmc   +1 more source

VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection. [PDF]

MethodsX
Kazi SS, Palkar B, Mishra D.
europepmc   +1 more source

KBNet: A Language and Vision Fusion Multi-Modal Framework for Rice Disease Segmentation. [PDF]

Plants (Basel)
Yan X, Zhou H, Zhu J, He M, Zhao T, Tan X, Zeng J.   +6 more
europepmc   +1 more source

YOLO-DP: A detection model of fifteen common rice diseases and pests. [PDF]

Sci Rep
Zhou T, Wei L.
europepmc   +1 more source