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ID 116326
著者
Liu, Wenjie Nantong University|Tokushima University
Wu, Guoqing Nantong University
キーワード
Multi-branch Fusion
Insect pest recognition
image classification
資料タイプ
学術雑誌論文
抄録
Earlier insect pest recognition is one of the critical factors for agricultural yield. Thus, an effective method to recognize the category of insect pests has become significant issues in the agricultural field. In this paper, we proposed a new residual block to learn multi-scale representation. In each block, it contains three branches: one is parameter-free, and the others contain several successive convolution layers. Moreover, we proposed a module and embedded it into the new residual block to recalibrate the channel-wise feature response and to model the relationship of the three branches. By stacking this kind of block, we constructed the Deep Multi-branch Fusion Residual Network (DMF-ResNet). For evaluating the model performance, we first test our model on CIFAR-10 and CIFAR-100 benchmark datasets. The experimental results show that DMF-ResNet outperforms the baseline models significantly. Then, we construct DMF-ResNet with different depths for high-resolution image classification tasks and apply it to recognize insect pests. We evaluate the model performance on the IP102 dataset, and the experimental results show that DMF-ResNet could achieve the best accuracy performance than the baseline models and other state-of-art methods. Based on these empirical experiments, we demonstrate the effectiveness of our approach.
掲載誌名
IEEE Transactions on Cognitive and Developmental Systems
ISSN
23798939
23798920
出版者
IEEE
13
3
開始ページ
705
終了ページ
716
発行日
2020-05-07
権利情報
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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出版社版DOI
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言語
eng
著者版フラグ
著者版
部局
理工学系