深度学习农作物检测的相关内容

文章 2024-09-15 来自：开发者社区

深度学习之农作物病害检测

基于深度学习的农作物病害检测利用卷积神经网络（CNN）、生成对抗网络（GAN）、Transformer等深度学习技术，自动识别和分类农作物的病害，帮助农业工作者提高作物管理效率、减少损失。 1. 农作物病害检测的挑战病害种类繁多：农作物病害的类型多样，不同病害在同一作物上的表现差异很大，同时同一种病害在不同生长阶段的症状也可能不同。环境影响：天气、光照、湿度等外部环境...

文章 2023-04-12 来自：开发者社区

m基于简化后的轻量级yolov4深度学习网络农作物检测算法matlab仿真

1.算法描述 YOLOv4 的深层网络包括 SPP 模块、PANet 模块、YOLO Head 模块和部分卷积，其主要作用是加强目标特征提取并获取预测结果。SPP 模块的输入端和输出端各连接一个三次卷积块，每个三次卷积块包含 2 个 1×1 卷积和 1 个 3×3 卷积。 PANet 模块包含特征层堆叠、上采样和下采样，每次堆叠后连接一个五次卷积块，每个五次卷积块包含 3 个 1×1 卷积...

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更新时间 2024-09-16 12:09:26

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