Results 131 to 140 of about 6,234 (203)

Deep learning networks-based tomato disease and pest detection: a first review of research studies using real field datasets. [PDF]

Front Plant Sci
Jelali M.
europepmc   +1 more source

The poplar pathogen <i>Sphaerulina musiva</i> has a dynamic genome architecture marked by chromosomal inversions and changes in transposable element abundance. [PDF]

Microb Genom
Zaccaron AZ, Lassagne A, Søndreli KL, Sudermann MA, Alcalá Briseño RI, Grünwald NJ, Weisberg AJ, LeBoldus JM.   +7 more
europepmc   +1 more source

BED-YOLO: An Enhanced YOLOv10n-Based Tomato Leaf Disease Detection Algorithm. [PDF]

Sensors (Basel)
Wang Q, Yan N, Qin Y, Zhang X, Li X.
europepmc   +1 more source

DGS-Yolov7-Tiny: a lightweight pest and disease target detection model suitable for edge computing environments. [PDF]

Sci Rep
Yu P, Zong B, Geng X, Yan H, Liu B, Chen C, Liu H, Xu X.   +7 more
europepmc   +1 more source

A multi-scale detection model for tomato leaf diseases with small target detection head. [PDF]

Front Plant Sci
Sun H, Li X, Li X, Wang X, Cheng Z, Al-Absi MA, Xiao L, Fu R.   +7 more
europepmc   +1 more source

Research on the intelligent detection model of plant diseases based on MamSwinNet. [PDF]

Front Plant Sci
Zhang A, Liu W.
europepmc   +1 more source

A novel hybrid fruit fly and simulated annealing optimized faster R-CNN for detection and classification of tomato plant leaf diseases. [PDF]

Sci Rep
Gangadevi E, Soufiane BO, Balusamy B, Khan F, Getahun M.   +4 more
europepmc   +1 more source

Tomato Leaf Disease Identification Framework FCMNet Based on Multimodal Fusion. [PDF]

Plants (Basel)
Deng S, Zhu J, Hu Y, He M, Xia Y.
europepmc   +1 more source

Identification of the Antagonistic Fungus <i>Diaporthe phoenicicola</i> Against Rhododendron Brown Spot Disease and Its Disease Control and Plant Growth-Promoting Efficacy. [PDF]

J Fungi (Basel)
Sun Y, Liu J, Li H, Zhu G, Zhu C, Lu J, Ma Y.   +6 more
europepmc   +1 more source

XSE-TomatoNet: An explainable AI based tomato leaf disease classification method using EfficientNetB0 with squeeze-and-excitation blocks and multi-scale feature fusion. [PDF]

MethodsX
Assaduzzaman M, Bishshash P, Nirob MAS, Marouf AA, Rokne JG, Alhajj R.   +5 more
europepmc   +1 more source