期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
基于卷积神经网络下昆虫种类图像识别应用研究 被引量:5
1
作者 魏甫豫 张振宇 梁桂珍 《河南师范大学学报(自然科学版)》 CAS 北大核心 2022年第6期96-105,共10页
昆虫种类图像识别是农业智能化识别虫害的重要方式,精准高效识别昆虫种类是进行针对性防治虫害的前提.利用昆虫数据集ArTaxOr及Insect_det,基于卷积神经网络下图像分类如MobileNet,ResNet及目标检测(FasterRCNN)、Yolo技术,运用迁移学... 昆虫种类图像识别是农业智能化识别虫害的重要方式,精准高效识别昆虫种类是进行针对性防治虫害的前提.利用昆虫数据集ArTaxOr及Insect_det,基于卷积神经网络下图像分类如MobileNet,ResNet及目标检测(FasterRCNN)、Yolo技术,运用迁移学习进行模型训练,并对比分析训练结果,获取最优昆虫种类图像识别模型.将构建的最优模型采用EasyEdge平台进行部署,从而实现了模型到端的全流程开发模式,为后续昆虫种类图像识别场景化应用研究提供依据参考. 展开更多
关键词 昆虫种类图像识别 卷积神经网络 图像分类 目标检测 模型场景应用
下载PDF
Bayesian moving object detection in dynamic scenes using an adaptive foreground model 被引量:1
2
作者 Sheng-yang YU Fang-lin WANG +1 位作者 Yun-feng XUE Jie YANG 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2009年第12期1750-1758,共9页
Accurate detection of moving objects is an important step in stable tracking or recognition. By using a nonparametric density estimation method over a joint domain-range representation of image pixels, the correlation... Accurate detection of moving objects is an important step in stable tracking or recognition. By using a nonparametric density estimation method over a joint domain-range representation of image pixels, the correlation between neighboring pixels can be used to achieve high levels of detection accuracy in the presence of dynamic background. However, color similarity between foreground and background will cause many foreground pixels to be misclassified. In this paper, an adaptive foreground model is exploited to detect moving objects in dynamic scenes. The foreground model provides an effective description of foreground by adaptively combining the temporal persistence and spatial coherence of moving objects. Building on the advantages of MAP-MRF (the maximum a posteriori in the Markov random field) decision framework, the proposed method performs well in addressing the challenging problem of missed detection caused by similarity in color between foreground and background pixels. Experimental results on real dynamic scenes show that the proposed method is robust and efficient. 展开更多
关键词 Moving object detection Foreground model Kernel density estimation (KDE) MAP-MRF estimation
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部