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

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

Determining chronicity and frequency of histologic lung lesions in feedyard cattle mortalities.

Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc·2026
Same author

Calcinosis Circumscripta with Iron Mineralization in an African Green Monkey (Chlorocebus aethiops sabaeus).

Journal of the American Association for Laboratory Animal Science : JAALAS·2025
Same author

Ocular and perineal squamous cell carcinomas in a Holstein Friesian cow.

Open veterinary journal·2024
Same author

Impact of psychiatric disorders on the risk of glioma: Mendelian randomization and biological annotation.

Journal of affective disorders·2024
Same author

Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition.

IEEE transactions on pattern analysis and machine intelligence·2024
Same author

Factorization Vision Transformer: Modeling Long-Range Dependency With Local Window Cost.

IEEE transactions on neural networks and learning systems·2023
Same journal

HardFlow: Hard-Constrained Sampling for Flow-Matching Models Via Trajectory Optimization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Industrial Brain: Self-Evolving Neuro-Symbolic Autonomy with Causal Resilience for Cyber-Physical Systems.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Adaptive Hardness-Driven Dictionary Distillation for Incomplete Streaming View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Mixture of Global and Local Experts with Diffusion Transformer for Controllable Face Generation.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Task-KV: Task-aware KV Cache Optimization via Semantic Differentiation of Attention Heads.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Achieving Text-based Person Retrieval with Any Granularity.

IEEE transactions on pattern analysis and machine intelligence·2026
查看所有相关文章

相关实验视频

Updated: Jun 12, 2025

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

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

376

低分辨率自我注意力用于语义细分

Yu-Huan Wu, Shi-Chen Zhang, Yun Liu

    IEEE transactions on pattern analysis and machine intelligence
    |June 10, 2025
    PubMed
    概括
    此摘要是机器生成的。

    本研究介绍了一种新的低分辨率自我注意力 (LRSA) 机制,用于高效的语义细分. 该LRFormer模型显著降低了计算成本,同时在基准数据集上实现了最先进的性能.

    更多相关视频

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    483
    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
    04:48

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

    Published on: November 30, 2022

    2.7K

    相关实验视频

    Last Updated: Jun 12, 2025

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

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    376
    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    483
    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
    04:48

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

    Published on: November 30, 2022

    2.7K

    科学领域:

    • 计算机视觉 计算机视觉
    • 人工智能的人工智能
    • 机器学习 机器学习

    背景情况:

    • 语义细分需要高分辨率的细节以获得像素准确度和全球背景以进行类预测.
    • 现有的视觉变压器由于高分辨率上下文建模而面临计算瓶.

    研究的目的:

    • 在语义细分中引入一个计算高效的机制来捕捉全球上下文.
    • 开发一种能解决当前模型计算局限性的视觉变压器.

    主要方法:

    • 开发了低分辨率自我注意力 (LRSA) 机制,用于全球上下文建模.
    • 在一个固定的低分辨率空间中计算自我注意力,并增加了高分辨率细节的深度卷.
    • 构建了LRFormer,一个采用LRSA机制的编码器-解码器视觉变压器.

    主要成果:

    • 与最先进的方法相比,LRFormer模型表现出卓越的性能.
    • 通过LRSA机制实现了计算成本 (FLOP) 的显著降低.
    • 在不同的数据集中验证了有效性:ADE20K,COCO-Stuff和Cityscapes.

    结论:

    • LRSA机制为语义细分提供了一种有效和高效的方法.
    • 对于高性能,低计算任务,LRFormer为现有的视觉变压器提供了一个有希望的替代方案.
    • 拟议的方法推进了计算机视觉的高效深度学习领域.