实体
发表于 2025-3-21 18:22:07
书目名称Computer Vision and Machine Learning in Agriculture, Volume 2影响因子(影响力)<br> http://impactfactor.cn/2024/if/?ISSN=BK0234068<br><br> <br><br>书目名称Computer Vision and Machine Learning in Agriculture, Volume 2影响因子(影响力)学科排名<br> http://impactfactor.cn/2024/ifr/?ISSN=BK0234068<br><br> <br><br>书目名称Computer Vision and Machine Learning in Agriculture, Volume 2网络公开度<br> http://impactfactor.cn/2024/at/?ISSN=BK0234068<br><br> <br><br>书目名称Computer Vision and Machine Learning in Agriculture, Volume 2网络公开度学科排名<br> http://impactfactor.cn/2024/atr/?ISSN=BK0234068<br><br> <br><br>书目名称Computer Vision and Machine Learning in Agriculture, Volume 2被引频次<br> http://impactfactor.cn/2024/tc/?ISSN=BK0234068<br><br> <br><br>书目名称Computer Vision and Machine Learning in Agriculture, Volume 2被引频次学科排名<br> http://impactfactor.cn/2024/tcr/?ISSN=BK0234068<br><br> <br><br>书目名称Computer Vision and Machine Learning in Agriculture, Volume 2年度引用<br> http://impactfactor.cn/2024/ii/?ISSN=BK0234068<br><br> <br><br>书目名称Computer Vision and Machine Learning in Agriculture, Volume 2年度引用学科排名<br> http://impactfactor.cn/2024/iir/?ISSN=BK0234068<br><br> <br><br>书目名称Computer Vision and Machine Learning in Agriculture, Volume 2读者反馈<br> http://impactfactor.cn/2024/5y/?ISSN=BK0234068<br><br> <br><br>书目名称Computer Vision and Machine Learning in Agriculture, Volume 2读者反馈学科排名<br> http://impactfactor.cn/2024/5yr/?ISSN=BK0234068<br><br> <br><br>
promote
发表于 2025-3-21 20:33:30
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Virtues
发表于 2025-3-22 00:30:38
Advanced Component Architecture,d coriander) and two different orchards (loquat and peach). The developed system outperformed its competitors with 91.3% mean average precision (mAP) and a processing time of 0.235 s. Thus, the proposed framework provided an excellent potential to be deployed on autonomous systems (UAVs, robots, etc
Bridle
发表于 2025-3-22 05:35:57
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abject
发表于 2025-3-22 12:18:41
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救护车
发表于 2025-3-22 14:10:42
Customizing Forms and Core Templates,essment. It can provide qualitative and quantitative data under single analysis. This chapter ensures a critical review on spectroscopic and imaging techniques combined chemo metric analysis, which achieves better accuracy of 99% for food quality analysis, role of machine learning and deep learning
救护车
发表于 2025-3-22 20:05:35
Using JSPs and Servlets in Stellent,detects and classifies input plant leaf data as healthy or diseased using SVM and kNN classifier, where SVM gives better accuracy of 93.67%. The obtained results indicate that the proposed methodology outperforms the other algorithms in obtaining good classification accuracy.
Minatory
发表于 2025-3-22 22:38:20
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粗糙
发表于 2025-3-23 05:12:40
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Lasting
发表于 2025-3-23 06:42:42
Customizing Forms and Core Templates, CNN-SVM classifier is shown to be a fast, extremely efficient method for classifying specific imaging features into desired disease classes, as well as giving preferable results over the plain CNN and other classifiers, such as the support vector machine (SVM) for large datasets. Finally, the exper