Галерея 3157481
Галерея 3157481
Прокси-сервер отказывается принимать соединения
Проверьте настройки прокси-сервера и убедитесь, что они верны.
Свяжитесь с вашим системным администратором и убедитесь, что прокси-сервер работает.
Firefox настроен на использование прокси-сервера, который отказывает в соединении.
Отправка сообщений о подобных ошибках поможет Mozilla обнаружить и заблокировать вредоносные сайты
Сообщить
Попробовать снова
Отправка сообщения
Сообщение отправлено
использует защитную технологию, которая является устаревшей и уязвимой для атаки. Злоумышленник может легко выявить информацию, которая, как вы думали, находится в безопасности.
National Center for Biotechnology Information
6-Fluoro-1H-benzoimidazole-2-carboxylic acid
5 Related Records Expand this section
8 Classification Expand this section
Computed by Lexichem TK 2.7.0 (PubChem release 2021.05.07)
Computed by InChI 1.0.6 (PubChem release 2021.05.07)
Computed by InChI 1.0.6 (PubChem release 2021.05.07)
Computed by OEChem 2.3.0 (PubChem release 2021.05.07)
Computed by PubChem 2.1 (PubChem release 2021.05.07)
6-Fluoro-1H-benzimidazole-2-carboxylic acid
5-FLUORO-1H-BENZIMIDAZOLE-2-CARBOXYLIC-ACID
6-Fluoro-1H-benzimidazole-2-carboxylic acid
PFAS and Fluorinated Compounds in PubChem
8600 Rockville Pike , Bethesda , MD , 20894 USA
PubChem ® is a registered trademark of the National Library of Medicine
6-Fluoro-1H-benzoimidazole-2-carboxylic acid
5-fluoro-1H-benzimidazole-2-carboxylic acid
6-fluoro-1H-benzimidazole-2-carboxylic acid
1H-Benzimidazole-2-carboxylicacid, 6-fluoro-
6-fluoro-1 H -benzimidazole-2-carboxylic acid
InChI=1S/C8H5FN2O2/c9-4-1-2-5-6(3-4)11-7(10-5)8(12)13/h1-3H,(H,10,11)(H,12,13)
Patents are available for this chemical structure:
Computed by PubChem 2.1 (PubChem release 2021.05.07)
Computed by XLogP3 3.0 (PubChem release 2021.05.07)
Computed by Cactvs 3.4.8.18 (PubChem release 2021.05.07)
Computed by Cactvs 3.4.8.18 (PubChem release 2021.05.07)
Computed by Cactvs 3.4.8.18 (PubChem release 2021.05.07)
Computed by PubChem 2.1 (PubChem release 2021.05.07)
Computed by PubChem 2.1 (PubChem release 2021.05.07)
Computed by Cactvs 3.4.8.18 (PubChem release 2021.05.07)
Computed by Cactvs 3.4.8.18 (PubChem release 2021.05.07)
Computed by PubChem (release 2012.11.26)
Copyright © 2016-2021 W. Robien, Inst. of Org. Chem., Univ. of Vienna. All Rights Reserved.
Alle Titel TV-Folgen Prominente Unternehmen Stichwörter Erweiterte Suche
Vollständig unterstützt English (United States) Teilweise unterstützt Diese Seite ist in der von dir ausgewählten Sprache nicht verfügbar. Français (Canada) Français (France) Deutsch (Deutschland) हिंदी (भारत) Italiano (Italia) Português (Brasil) Español (España) Español (México)
Filmography
by Year
by Job
by Ratings
by Votes
by Genre
by Keyword
Did You Know?
Personal Quotes
Trivia
Trademark
Photo & Video
Photo Gallery
Trailers and Videos
Opinion
Awards
Related Items
Credited With
News
External Sites
Professional Services
Get more at IMDbPro
Melde dich an für Zugriff auf mehr Inhalte Melde dich an für Zugriff auf mehr Inhalte
Anne Peterson is known for Darling (2007).
Other Works
|
Publicity Listings
|
Official Sites
All Books Conferences Courses Journals & Magazines Standards Authors Citations
Abstract: Weakly supervised semantic segmentation with only image-level labels aims to reduce annotation costs for the segmentation task. Existing approaches generally leverage cla... View more
Weakly supervised semantic segmentation with only image-level labels aims to reduce annotation costs for the segmentation task. Existing approaches generally leverage class activation maps (CAMs) to locate the object regions for pseudo label generation. However, CAMs can only discover the most discriminative parts of objects, thus leading to inferior pixel-level pseudo labels. To address this issue, we propose a saliency guided I nter- and I ntra- C lass R elation C onstrained (I 2 CRC) framework to assist the expansion of the activated object regions in CAMs. Specifically, we propose a saliency guided class-agnostic distance module to pull the intra-category features closer by aligning features to their class prototypes. Further, we propose a class-specific distance module to push the inter-class features apart and encourage the object region to have a higher activation than the background. Besides strengthening the capability of the classification network to activate more integral object regions in CAMs, we also introduce an object guided label refinement module to take a full use of both the segmentation prediction and the initial labels for obtaining superior pseudo-labels. Extensive experiments on PASCAL VOC 2012 and COCO datasets demonstrate well the effectiveness of I 2 CRC over other state-of-the-art counterparts.
Published in: IEEE Transactions on Multimedia ( Early Access )
IEEE Account
Change Username/Password
Update Address
Purchase Details
Payment Options
Order History
View Purchased Documents
Need Help?
US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2023 IEEE - All rights reserved.
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. © Copyright 2023 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
Большой член ебет блониднку с большими сиськами
Приятная голая пизденка крупным планом
Ебет жгучую брюнетку на офисном столе