宣告无效
发表于 2025-3-21 17:21:10
书目名称Intelligent Computing Methodologies影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0469460<br><br> <br><br>书目名称Intelligent Computing Methodologies影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0469460<br><br> <br><br>书目名称Intelligent Computing Methodologies网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0469460<br><br> <br><br>书目名称Intelligent Computing Methodologies网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0469460<br><br> <br><br>书目名称Intelligent Computing Methodologies被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0469460<br><br> <br><br>书目名称Intelligent Computing Methodologies被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0469460<br><br> <br><br>书目名称Intelligent Computing Methodologies年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0469460<br><br> <br><br>书目名称Intelligent Computing Methodologies年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0469460<br><br> <br><br>书目名称Intelligent Computing Methodologies读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0469460<br><br> <br><br>书目名称Intelligent Computing Methodologies读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0469460<br><br> <br><br>
灾祸
发表于 2025-3-21 21:15:51
Intelligent Computing Methodologies978-3-030-60796-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
COKE
发表于 2025-3-22 02:00:16
https://doi.org/10.1007/978-3-030-60796-8classification; clustering algorithms; computer networks; computer vision; correlation analysis; data min
MUTED
发表于 2025-3-22 07:07:30
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ellagic-acid
发表于 2025-3-22 08:42:31
Identification of Diseases and Pests in Tomato Plants Through Artificial Visionhas been applied to the dataset, obtaining texture descriptors with the Haralick and LBP algorithm, and chromatic descriptors through the Hu moments, Fourier descriptors, discrete cosine transform DCT and Gabor characteristics; finally, classification algorithms such as: SVM, Backpropagation, Naive
Bereavement
发表于 2025-3-22 15:29:11
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箴言
发表于 2025-3-22 20:05:08
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lobster
发表于 2025-3-22 22:28:15
LiDAR-Camera-Based Deep Dense Fusion for Robust 3D Object Detectionti-sensor-based methods on all three classes on moderate difficulty (3D/BEV): Car (75.60%/88.65%), Pedestrian (64.36%/66.98%), Cyclist (57.53%/57.30%). Specifically, the DDF3D greatly improves the detection accuracy of hard difficulty in 2D detection with an 88.19% accuracy for the car class.
热情赞扬
发表于 2025-3-23 04:01:05
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CORE
发表于 2025-3-23 07:35:01
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