Effective Insect Recognition Based on Deep Neural Network Models in Complex Background-Reference-Cited by-同舟云学术

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Effective Insect Recognition Based on Deep Neural Network Models in Complex Background

Published:2021-06-18 Issue: Volume: Page:
ISSN:
Container-title:2021 5th International Conference on High Performance Compilation, Computing and Communications
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Author:

Yang Fan¹,Li Feifei²,Xu Jie¹,Su Guanghui¹,Li Jianhui³,Ji Meng⁴,Xiong Wenjie⁴,Zhao Bo⁴

Affiliation:

1. University of Electronic Science and Technology of China, China

2. Chengdu Xingyinian Intelligent Technology Co.LTD, China

3. Chengdu Forest Pest Control and Quarantine Station, China

4. Qionglai Municipal Bureau of Planning and Natural Resources, China

Funder

Chengdu Science and Technology Project

Natural Science Foundation of China

The 2020 Special funds for forestry industry development

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3471274.3471285

Reference19 articles.

1. IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition

2. Development of Application for Forest Insect Classification using CNN

3. Family-Based Big Medical-Level Data Acquisition System

4. A new ranking algorithm and an evolutionary model based on comprehensive weighted clique degree for complex network

5. A novel batch-based LKH tree balanced algorithm for group key management

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1. ARTIFICIAL INTELLIGENCE AND ITS TOOLS IN PEST CONTROL FOR AGRICULTURAL PRODUCTION: A REVIEW;RECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218;2024-05-27

2. Artificial neuronal networks are revolutionizing entomological research;Journal of Applied Entomology;2024-01-10

3. Multi-class Classification of Insects using Deep Neural Networks;2023 International Conference on Computer Communication and Informatics (ICCCI);2023-01-23

4. Next generation insect taxonomic classification by comparing different deep learning algorithms;PLOS ONE;2022-12-30

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