An Effective Data Augmentation Strategy for CNN-Based Pest Localization and Recognition in the Field

An Effective Data Augmentation Strategy for CNN-Based Pest Localization and Recognition in the Field

In agriculture, pest always causes the major damage in fields and results in significant crop yield losses. Currently, manual pest classification and counting are very time-consuming and many subjective factors can affect the population counting accuracy. In addition, the existing pest localization...

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Bibliographic Details
Main Authors: Rui Li, Rujing Wang, Jie Zhang, Chengjun Xie, Liu Liu, Fangyuan Wang, Hongbo Chen, Tianjiao Chen, Haiying Hu, Xiufang Jia, Min Hu, Man Zhou, Dengshan Li, Wancai Liu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Pest localization
pest recognition
convolutional neural network
multi-scale
data augmentation
Online Access:https://ieeexplore.ieee.org/document/8884206/

Internet

https://ieeexplore.ieee.org/document/8884206/

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