Efficient Convolutional Neural Network for Pest Recognition-ExquisiteNet

Shi Yao Zhou, Chung Yen Su

研究成果: 書貢獻/報告類型會議論文篇章

摘要

Nowadays, due to the rapid population expansion, food shortage has become a critical issue. To stabilize food production, preventing crops from being attacked by pests is very important. In general, farmers use pesticides, however, the improper use also kills insects such as bees that are beneficial to crops. If the number of bees is too few, the supplement of food in the world will be short. Besides, excessive pesticides seriously pollute the environment. Accordingly, farmers need a machine that automatically recognizes the pests. Recently, deep learning is popular because of its effectiveness in the field of image classification. In this paper, we propose an efficient model called ExquisiteNet to recognize the pests. ExquisiteNet mainly consists of two blocks. One is double fusion with squeeze-and-excitation-bottleneck block (DFSEB block), and the other is max feature expansion block (ME block). ExquisiteNet only has 0.98 M parameters and its computing speed is fast almost the same as SqueezeNet. To evaluate our model's performance, the model is testedd on a benchmark pest dataset called IP102. The model achieves a higher accuracy of 52.32% on the test set of IP102 without any data augmentation than that of many state-of-the-art models such as ResNet101, ShuffleNetV2, MobileNetV3-large, EfficientNet, and so on.

原文英語
主出版物標題2nd IEEE Eurasia Conference on IOT, Communication and Engineering 2020, ECICE 2020
編輯Teen-Hang Meen
發行者Institute of Electrical and Electronics Engineers Inc.
頁面216-219
頁數4
ISBN(電子)9781728180601
DOIs
出版狀態已發佈 - 2020 十月 23
事件2nd IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2020 - Yunlin, 臺灣
持續時間: 2020 十月 232020 十月 25

出版系列

名字2nd IEEE Eurasia Conference on IOT, Communication and Engineering 2020, ECICE 2020

會議

會議2nd IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2020
國家/地區臺灣
城市Yunlin
期間2020/10/232020/10/25

ASJC Scopus subject areas

  • 人工智慧
  • 電腦網路與通信
  • 電腦科學應用
  • 訊號處理
  • 生物醫學工程
  • 電氣與電子工程
  • 控制和優化
  • 儀器

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