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: Marine Protists; Diversity and Dynami Susumu Ohtsuka,Toshinobu Suzaki,Fabrice Not Book 2015 Springer Japan 2015 Aquatic ecosystem.Chemosynt

[復(fù)制鏈接]
樓主: 街道
11#
發(fā)表于 2025-3-23 12:39:02 | 只看該作者
Nigel Grimsley,Sheree Yau,Gwena?l Piganeau,Hervé Moreauentation datasets demonstrate state-of-the-art performance. Notably, our method achieves a Dice score of 91.31% with only 20% labeled data, which is remarkably close to the 91.62% score of the fully supervised method that uses 100% labeled data on the left atrium dataset. Our framework has the poten
12#
發(fā)表于 2025-3-23 15:21:28 | 只看該作者
13#
發(fā)表于 2025-3-23 19:55:21 | 只看該作者
14#
發(fā)表于 2025-3-24 00:16:17 | 只看該作者
Yasuhide Nakamura,Noritoshi Suzuki help the meta guided network automatically learn the pixel transition confidence map in an alternative training manner. Experiments have been conducted on three medical image datasets, and the results demonstrate that our method is able to achieve superior segmentation with noisy labels compared to
15#
發(fā)表于 2025-3-24 02:59:45 | 只看該作者
Akira Kuwata,David H. Jewson help the meta guided network automatically learn the pixel transition confidence map in an alternative training manner. Experiments have been conducted on three medical image datasets, and the results demonstrate that our method is able to achieve superior segmentation with noisy labels compared to
16#
發(fā)表于 2025-3-24 09:32:52 | 只看該作者
Takashi Kamiyamas for a weakly-supervised self-training scheme. The self-training is done across multiple rounds to improve the model’s robustness against noise. Two experiments were conducted with static and variable thresholds during self-training, and we show that sensitivity improves from 72.5% without self-tra
17#
發(fā)表于 2025-3-24 11:55:48 | 只看該作者
18#
發(fā)表于 2025-3-24 18:42:32 | 只看該作者
19#
發(fā)表于 2025-3-24 21:17:28 | 只看該作者
20#
發(fā)表于 2025-3-25 02:21:09 | 只看該作者
 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(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-27 02:52
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
兰溪市| 汕头市| 保亭| 郎溪县| 鹿泉市| 龙陵县| 高淳县| 天峨县| 白城市| 定日县| 河池市| 灌云县| 凤翔县| 富裕县| 剑河县| 玛纳斯县| 安仁县| 新竹市| 登封市| 彝良县| 金秀| 海伦市| 黄冈市| 寻甸| 东方市| 苏尼特左旗| 武义县| 牡丹江市| 锡林郭勒盟| 财经| 土默特左旗| 建昌县| 贵定县| 常德市| 岐山县| 陇川县| 调兵山市| 威远县| 玉树县| 南郑县| 大兴区|