找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Machine Learning in Medical Imaging; 12th International W Chunfeng Lian,Xiaohuan Cao,Pingkun Yan Conference proceedings 2021 Springer Natur

[復(fù)制鏈接]
查看: 29661|回復(fù): 63
樓主
發(fā)表于 2025-3-21 17:09:45 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Machine Learning in Medical Imaging
副標(biāo)題12th International W
編輯Chunfeng Lian,Xiaohuan Cao,Pingkun Yan
視頻videohttp://file.papertrans.cn/621/620678/620678.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Machine Learning in Medical Imaging; 12th International W Chunfeng Lian,Xiaohuan Cao,Pingkun Yan Conference proceedings 2021 Springer Natur
描述This book constitutes the proceedings of the 12th International Workshop on Machine Learning in Medical Imaging, MLMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.*.The 71 papers presented in this volume were carefully reviewed and selected from 92 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc. .*The workshop was held virtually..
出版日期Conference proceedings 2021
關(guān)鍵詞artificial intelligence; big medical imaging data analytics; bioinformatics; cellular image analysis; co
版次1
doihttps://doi.org/10.1007/978-3-030-87589-3
isbn_softcover978-3-030-87588-6
isbn_ebook978-3-030-87589-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

書目名稱Machine Learning in Medical Imaging影響因子(影響力)




書目名稱Machine Learning in Medical Imaging影響因子(影響力)學(xué)科排名




書目名稱Machine Learning in Medical Imaging網(wǎng)絡(luò)公開度




書目名稱Machine Learning in Medical Imaging網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Machine Learning in Medical Imaging被引頻次




書目名稱Machine Learning in Medical Imaging被引頻次學(xué)科排名




書目名稱Machine Learning in Medical Imaging年度引用




書目名稱Machine Learning in Medical Imaging年度引用學(xué)科排名




書目名稱Machine Learning in Medical Imaging讀者反饋




書目名稱Machine Learning in Medical Imaging讀者反饋學(xué)科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶組沒有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 20:22:04 | 只看該作者
Machine Learning in Medical Imaging978-3-030-87589-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
板凳
發(fā)表于 2025-3-22 01:26:38 | 只看該作者
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/m/image/620678.jpg
地板
發(fā)表于 2025-3-22 07:04:09 | 只看該作者
https://doi.org/10.1007/978-3-030-87589-3artificial intelligence; big medical imaging data analytics; bioinformatics; cellular image analysis; co
5#
發(fā)表于 2025-3-22 12:17:55 | 只看該作者
6#
發(fā)表于 2025-3-22 14:28:29 | 只看該作者
Tapabrata Chakraborti,Fergus Gleeson,Jens Rittscher many technology generations of semiconductor logic and memoLife-Cycle Assessment of Semiconductors presents the first and thus far only available transparent and complete life cycle assessment of semiconductor devices. A lack of reliable semiconductor LCA data has been a major challenge to evaluati
7#
發(fā)表于 2025-3-22 19:23:51 | 只看該作者
Hao Guan,Li Wang,Dongren Yao,Andrea Bozoki,Mingxia Liu many technology generations of semiconductor logic and memoLife-Cycle Assessment of Semiconductors presents the first and thus far only available transparent and complete life cycle assessment of semiconductor devices. A lack of reliable semiconductor LCA data has been a major challenge to evaluati
8#
發(fā)表于 2025-3-22 21:26:23 | 只看該作者
9#
發(fā)表于 2025-3-23 03:51:32 | 只看該作者
10#
發(fā)表于 2025-3-23 05:55:54 | 只看該作者
Jie Wei,Yongsheng Pan,Yong Xia,Dinggang Shench and gestures in making Human—Virtual Human interfaces more effective. Miller [33] suggests that only 7% of a message is sent through words: the remainder is sent through facial expressions (55%) and vocal intonation (38%). Therefore in both analysis of human conversations and in the synthesis of
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-18 16:47
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
钦州市| 南通市| 黄山市| 吉水县| 鲜城| 新乐市| 咸宁市| 荆州市| 阜新| 台州市| 林口县| 交口县| 大化| 科技| 邻水| 林芝县| 扶沟县| 驻马店市| 白银市| 腾冲县| 寿宁县| 城市| 绍兴县| 丹凤县| 霞浦县| 邻水| 玛沁县| 庆元县| 南阳市| 武威市| 棋牌| 武乡县| 永安市| 六盘水市| 颍上县| 彰化市| 聂荣县| 都兰县| 泰兴市| 霍城县| 阿巴嘎旗|