Advancing Image Recognition: Towards Lightweight Few-shot Learning Model for Maize Seedling Detection
Author:
Affiliation:
1. Henan Mechanical Electrical Vocational College, China and SEGi University, Malaysia
2. Built Environment and Information Technology, SEGi University, Malaysia
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3685088.3685198
Reference7 articles.
1. Revolutionizing crop disease detection with computational deep learning: a comprehensive review
2. Nitin and Gupta S.B. 2023. Artificial intelligence in smart agriculture: Applications and challenges. Current Applied Science and Technology. (Nov. 2023) e0254427. DOI: https://doi.org/10.55003/cast.2023.254427.
3. Few-Shot Learning approach for plant disease classification using images taken in the field
4. Dong X. Yan S. and Duan C. 2022. A lightweight vehicles detection network model based on YOLOv5. Engineering Applications of Artificial Intelligence. 113 (Aug. 2022) 104914. DOI: https://doi.org/10.1016/j.engappai.2022.104914.
5. Principal Component Networks: Utilizing Low-Rank Activation Structure to Reduce Parameters Early in Training
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