凭票入场 发表于 2025-3-21 16:49:38

书目名称Information Technology in Biomedicine影响因子(影响力)<br>        http://figure.impactfactor.cn/if/?ISSN=BK0465712<br><br>        <br><br>书目名称Information Technology in Biomedicine影响因子(影响力)学科排名<br>        http://figure.impactfactor.cn/ifr/?ISSN=BK0465712<br><br>        <br><br>书目名称Information Technology in Biomedicine网络公开度<br>        http://figure.impactfactor.cn/at/?ISSN=BK0465712<br><br>        <br><br>书目名称Information Technology in Biomedicine网络公开度学科排名<br>        http://figure.impactfactor.cn/atr/?ISSN=BK0465712<br><br>        <br><br>书目名称Information Technology in Biomedicine被引频次<br>        http://figure.impactfactor.cn/tc/?ISSN=BK0465712<br><br>        <br><br>书目名称Information Technology in Biomedicine被引频次学科排名<br>        http://figure.impactfactor.cn/tcr/?ISSN=BK0465712<br><br>        <br><br>书目名称Information Technology in Biomedicine年度引用<br>        http://figure.impactfactor.cn/ii/?ISSN=BK0465712<br><br>        <br><br>书目名称Information Technology in Biomedicine年度引用学科排名<br>        http://figure.impactfactor.cn/iir/?ISSN=BK0465712<br><br>        <br><br>书目名称Information Technology in Biomedicine读者反馈<br>        http://figure.impactfactor.cn/5y/?ISSN=BK0465712<br><br>        <br><br>书目名称Information Technology in Biomedicine读者反馈学科排名<br>        http://figure.impactfactor.cn/5yr/?ISSN=BK0465712<br><br>        <br><br>

大量 发表于 2025-3-21 22:02:09

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voluble 发表于 2025-3-22 00:59:21

MRFU-Net: A Multiple Receptive Field U-Net for Environmental Microorganism Image SegmentationThe MRFU-Net is an improved deep learning structure based on U-Net and Inception. In the experiment, in contrast to the original U-Net, the overall segmentation performance of Dice, Jaccard, recall and accuracy increases from ., ., . and . to ., ., . and ., respectively. The overall volume overlap e

奖牌 发表于 2025-3-22 06:26:09

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nonradioactive 发表于 2025-3-22 10:43:29

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duplicate 发表于 2025-3-22 15:12:43

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Condescending 发表于 2025-3-22 20:48:06

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cornucopia 发表于 2025-3-22 21:35:59

Pancreas and Duodenum—Automated Organ Segmentationc extraction of pancreas and duodenum in clinical abdominal computed tomography (CT) scans. The proposed method allows building a feature vector that automates and streamlines the fuzzy connectedness (FC) method. All described steps of the presented methodology have been implemented in MATLAB and te

刚毅 发表于 2025-3-23 04:00:24

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CRUDE 发表于 2025-3-23 09:06:44

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查看完整版本: Titlebook: Information Technology in Biomedicine; Ewa Pietka,Pawel Badura,Wojciech Wieclawek Book 2021 The Editor(s) (if applicable) and The Author(s