purulent
发表于 2025-3-21 19:55:24
书目名称Advances in Brain Inspired Cognitive Systems影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0146953<br><br> <br><br>书目名称Advances in Brain Inspired Cognitive Systems影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0146953<br><br> <br><br>书目名称Advances in Brain Inspired Cognitive Systems网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0146953<br><br> <br><br>书目名称Advances in Brain Inspired Cognitive Systems网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0146953<br><br> <br><br>书目名称Advances in Brain Inspired Cognitive Systems被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0146953<br><br> <br><br>书目名称Advances in Brain Inspired Cognitive Systems被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0146953<br><br> <br><br>书目名称Advances in Brain Inspired Cognitive Systems年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0146953<br><br> <br><br>书目名称Advances in Brain Inspired Cognitive Systems年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0146953<br><br> <br><br>书目名称Advances in Brain Inspired Cognitive Systems读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0146953<br><br> <br><br>书目名称Advances in Brain Inspired Cognitive Systems读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0146953<br><br> <br><br>
Aspirin
发表于 2025-3-21 23:50:01
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FLACK
发表于 2025-3-22 04:17:16
André Borrmann,Markus König,Jakob Beetzale segmentation. It constructs a multi-scale fusion saliency detection algorithm. The experimental results show that the proposed method achieves better than seven classical saliency detection algorithms on four data sets.
ostrish
发表于 2025-3-22 05:41:10
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流动才波动
发表于 2025-3-22 11:40:53
Ausarbeitungsgrade von BIM-Modellenection of ESA. To fill the gap of the lack of benchmark datasets, we create a composite dataset ESAD based on existing datasets for ESA detection. Extensive experiments demonstrate that the proposed method is effective for accurate ESA detection, outperforming many baseline methods.
和谐
发表于 2025-3-22 12:57:22
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无效
发表于 2025-3-22 18:12:41
Process-Based Definition of Model Contente training process dynamically, and the cross-entropy loss function of the original model was replaced with a mixed loss function composed of Focal loss and Dice loss. The results show that E-measure, S-measure, F-measure, and MAE improve the seven existing public RGB-D datasets.
尽管
发表于 2025-3-22 22:03:39
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显微镜
发表于 2025-3-23 05:27:39
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prostate-gland
发表于 2025-3-23 09:03:33
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