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相关概念视频

Force Classification01:22

Force Classification

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Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
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A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
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原型适配器:高效的免训练的CLIP适配器,用于少数拍摄图像分类.

Naoki Kato1, Yoshiki Nota2, Yoshimitsu Aoki1

  • 1Department of Electrical Engineering, Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Kanagawa, Japan.

Sensors (Basel, Switzerland)
|June 19, 2024
PubMed
概括
此摘要是机器生成的。

原始适配器增强了像CLIP这样的大型视觉语言模型的几次拍摄识别. 这种方法使用基于类原型的恒定尺寸适配器,性能优于以前的方法,并使得部署效率高.

关键词:
几次射击的学习学习基础模型 基础模型图像的分类图像的分类.

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科学领域:

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

背景情况:

  • 大型视觉语言模型 (例如,CLIP) 在零射击传输方面表现出色.
  • 短暂的识别需要将模型适应有限的数据.
  • 像Tip-Adapter这样的现有方法可以提高几次拍摄的性能,但由于适配器尺寸大,面临可扩展性问题.

研究的目的:

  • 为CLIP提出一种新的,高效的适应方法.
  • 开发一个恒定尺寸的适配器,克服Tip-Adapter的可扩展性限制.
  • 增强少数镜头分类性能,重点关注歧视性决策边界.

主要方法:

  • 介绍了Proto-Adapter,这是一个具有恒定大小的单层适配器.
  • 使用来自类特征聚合的原型表示来构建适配器重量.
  • 在微调过程中实施了距离边缘罚款,以增加类间差异.

主要成果:

  • 与Tip-Adapter相比,Proto-Adapter实现了优越的几次射击识别性能.
  • 拟议的方法在少数拍摄分类任务中在各种数据集中表现出有效性.
  • 不变的适配器尺寸确保了高效的部署,无论训练数据量如何.

结论:

  • Proto-Adapter提供了一种有效且可扩展的解决方案,用于对大型视觉语言模型进行短时间的适应.
  • 基于原型的方法和距离边缘罚款有助于改善模型的可区分性.
  • 这种方法促进了实际应用,需要使用有限的数据进行高效的少量学习.