Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Stereotype Content Model02:16

Stereotype Content Model

14.0K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.0K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Beyond biochemical control: headache resolution with pasireotide in a patient with acromegaly and residual tumor.

JCEM case reports·2026
Same author

Systematic Review and Exploratory Meta-Analysis of AI-Enabled and Digital Technology-Assisted Interventions for Dental Anxiety During Dental Treatment.

Depression and anxiety·2026
Same author

The effects of locally administered aminophylline in patients undergoing ureteroscopic lithotripsy: a systematic review with exploratory meta-analysis.

Frontiers in urology·2026
Same author

Combined TIRF and 3D Super-Resolution Microscopy for Nanoscopic Characterization of Adhesion Molecules on Microvilli.

Analytical chemistry·2026
Same author

Furosemide induces dose-dependent testicular toxicity via disrupting blood-testis barrier, inflammation, and apoptosis: A comprehensive biochemical, hormonal, and histopathological study.

Tissue & cell·2026
Same author

Machine learning based prediction of recurrence in oral tongue cancer: a systematic review with quantitative synthesis.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery·2026

相关实验视频

Updated: Jun 5, 2025

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.7K

使用层次式风格传输网络扩展图像风格化的用户控制.

Sunder Ali Khowaja1, Sultan Almakdi2, Muhammad Ali Memon3

  • 1Department of Telecommunication, Faculty of Eng. And Tech, University of Sindh, Jamshoro, Sindh, 76090, Pakistan.

Heliyon
|December 13, 2024
PubMed
概括

本研究介绍了图像风格化的层次式风格传输网络 (HSTN),为用户提供对风格强度的控制. HSTN增强了细节的保存和风格的融合,优于现有的方法.

关键词:
拒绝这种行为是拒绝的.固定点控制损失 固定点控制损失一个层次化的网络网络.神经风格转移神经风格转移用户控制用户控制.

更多相关视频

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

368
A Human Cerebral Organoid Model of Neural Cell Transplantation
08:58

A Human Cerebral Organoid Model of Neural Cell Transplantation

Published on: July 21, 2023

1.1K

相关实验视频

Last Updated: Jun 5, 2025

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.7K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

368
A Human Cerebral Organoid Model of Neural Cell Transplantation
08:58

A Human Cerebral Organoid Model of Neural Cell Transplantation

Published on: July 21, 2023

1.1K

科学领域:

  • 计算机视觉 计算机视觉
  • 人工智能的人工智能
  • 图像处理 图像处理

背景情况:

  • 神经风格转移使用风格图像特征重新呈现内容图像.
  • 现有的方法往往缺乏用户对风格强度和细节保存的控制.
  • 以前的方法利用感知和固定点内容损失,限制了风格自由.

研究的目的:

  • 为图像造型提出层次式风格传输网络 (HSTN).
  • 为了让用户可以通过一个denoising参数来控制应用的风格程度.
  • 为了提高在风格化过程中内容图像细节的保存.

主要方法:

  • 开发了层次式风格传输网络 (HSTN).
  • 包含一个固定点控制损失,以保存细节.
  • 集成了一个拒绝CNN网络 (DnCNN) 和拒绝风格控制的损失.
  • 使用编码器解码器,DnCNN和丢失网络块.

主要成果:

  • 与现有的方法相比,HSTN展示了风格和内容保存的优越融合.
  • 在用户评价中,它比第二个表现最好的方法获得了12%的更好的结果.
  • 在内容 (37.64%) 和风格 (60.27%) 分类分数之间取得了有利的权衡.

结论:

  • 在控制风格强度方面,HSTN为用户提供了显著的自由.
  • 拟议的方法在保持内容细节的同时实现有效的风格转移方面表现出色.
  • HSTN代表了可控制和高保真图像风格化的新方法.