PlantViQ: Disease Recognition Across Varied Environments with Vision Transformer and Quadrangle Attention

Author:

Li ShutingORCID,Chen BaoyuORCID,Li FengORCID,He JingmeiORCID,He FeiyongORCID,Hu YingbiaoORCID,Chen JingjiaORCID,Li HuinianORCID

Publisher

Springer Nature Singapore

Reference22 articles.

1. Faithpraise, F., Birch, P., Young, R., Obu, J., Faithpraise, B., Chatwin, C.: Automatic plant pest detection and recognition using k-means clustering algorithm and correspondence filters. Int. J. Adv. Biotechnol. Res. 4, 189–199 (2013)

2. Mohanty, S.P., Hughes, D.P., Salathé, M.: Using deep learning for image-based plant disease detection. Front. Plant Sci. 7, 215232 (2016)

3. Arnal Barbedo, J.G.: Digital image processing techniques for detecting, quantifying and classifying plant diseases. Springerplus 2, 660 (2013)

4. Maryum, A., Akram, M.U., Salam, A.A.: Cassava leaf disease classification using deep neural networks. In: 2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET), pp. 32–37 (2021)

5. Sambasivam, G., Opiyo, G.D.: A predictive machine learning application in agriculture: cassava disease detection and classification with imbalanced dataset using convolutional neural networks. Egypt. Inf. J. 22, 27–34 (2021)

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