Classification of Weeds and Crops at the Pixel-Level Using Convolutional Neural Networks and Data Augmentation-Reference-Cited by-同舟云学术

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Classification of Weeds and Crops at the Pixel-Level Using Convolutional Neural Networks and Data Augmentation

Published:2019-11 Issue: Volume: Page:
ISSN:
Container-title:2019 IEEE Latin American Conference on Computational Intelligence (LA-CCI)
language:
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Author:

Brilhador Anderson,Gutoski Matheus,Hattori Leandro Takeshi,de Souza Inacio Andrei,Lazzaretti Andre Eugenio,Lopes Heitor Silverio

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9028002/9036753/09037044.pdf?arnumber=9037044

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. YOLOv8n-Seg for Crop Weeds Detection and Instance Segmentation;2024 2nd International Conference on Electrical Engineering and Automatic Control (ICEEAC);2024-05-12

2. Crop and Weed Segmentation and Fractal Dimension Estimation Using Small Training Data in Heterogeneous Data Environment;Fractal and Fractional;2024-05-10

3. SC-Net: A new strip convolutional network model for rice seedling and weed segmentation in paddy field;Computers and Electronics in Agriculture;2024-05

4. Weed Detection from Unmanned Aerial Vehicle Imagery Using Deep Learning—A Comparison between High-End and Low-Cost Multispectral Sensors;Sensors;2024-02-28

5. Deep Learning Techniques for Weed Detection in Agricultural Environments: A Comprehensive Review;IEEE Access;2024

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