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

Aggregates Classification01:29

Aggregates Classification

387
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
387
Force Classification01:22

Force Classification

1.6K
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,...
1.6K
Classification of Systems-I01:26

Classification of Systems-I

314
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
314
Functional Classification of Joints01:09

Functional Classification of Joints

4.9K
Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
4.9K
Classification of Systems-II01:31

Classification of Systems-II

242
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
242
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

150
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
150

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

A machine learning approach for type 2 diabetes diagnosis and prognosis using tailored heterogeneous feature subsets.

Medical & biological engineering & computing·2025
Same author

Breast Delineation in Full-Field Digital Mammography Using the Segment Anything Model.

Diagnostics (Basel, Switzerland)·2024
Same author

Breast Dense Tissue Segmentation with Noisy Labels: A Hybrid Threshold-Based and Mask-Based Approach.

Diagnostics (Basel, Switzerland)·2022
Same author

Decision support through risk cost estimation in 30-day hospital unplanned readmission.

PloS one·2022
Same author

High-Profile VRU Detection on Resource-Constrained Hardware Using YOLOv3/v4 on BDD100K.

Journal of imaging·2021
Same author

Probabilistic Evaluation of 3D Surfaces Using Statistical Shape Models (SSM).

Sensors (Basel, Switzerland)·2020

相关实验视频

Updated: Sep 16, 2025

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development
13:01

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

34.1K

通过视图兼容特征融合进行对象特定多视图分类.

Javier Perez Soler1, Jose-Luis Guardiola2, Nicolás García Sastre1

  • 1Instituto Tecnológico de Informática (ITI), C. Nicolás Copérnico, 7, 46022 Valencia, Spain.

Sensors (Basel, Switzerland)
|July 12, 2025
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的视图兼容特征融合 (VCFF) 方法,用于多视图分类 (MVC). 在工业环境中,VCFF准确地将特定对象与未知物区分开来,在开放场景中表现优于现有的方法.

关键词:
功能融合功能融合功能工业检查 工业检查 工业检查多视图分类的多视图分类一个开放式的分类.

更多相关视频

Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.1K
Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.4K

相关实验视频

Last Updated: Sep 16, 2025

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development
13:01

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

34.1K
Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.1K
Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.4K

科学领域:

  • 计算机视觉 计算机视觉
  • 机器学习 机器学习
  • 工业自动化 工业自动化

背景情况:

  • 多视图分类 (MVC) 通常使用多个视角对象进行分类.
  • 工业检查等现实应用需要将特定对象与未知对象区分开来,这对目前的封闭式MVC方法来说是一个挑战.
  • 现有的MVC方法通常是通用化的,但在识别单个对象和丢弃新对象方面存在困难.

研究的目的:

  • 开发一种有效的多视图分类方法,用于识别工业质量控制中的特定对象.
  • 在开放场景和工业检查中解决现有的MVC方法的局限性.
  • 引入一种新的方法,该方法明确整合特征融合的构成信息.

主要方法:

  • 提出了一种视图兼容特征融合 (VCFF) 方法,用于多视图分类.
  • 将姿势信息,特别是基于相对姿势的旋转信息集成到特征融合过程中.
  • 从预先确定的位置使用图像来准确分类特定的物体.

主要成果:

  • VCFF显著优于最先进的MVC算法,特别是在开放式场景中.
  • 使用8个摄像头达到1.0的平均精度,而使用20个摄像头达到0.95的现有方法.
  • 在工业检查场景中,通过8个摄像头获得了1.0的完美AUC-ROC得分,超过了之前的方法 (0.72).
  • 证明了非常准确的旋转估计,误差幅度略高于2°.

结论:

  • 拟议的VCFF方法为工业检查和质量控制中的多视图分类提供了强大的解决方案.
  • VCFF明确集成的姿势信息增强了特征融合和分类准确性,特别是在开放的条件下.
  • 与现有的MVC方法相比,VCFF提供了更高的性能和效率,特别是在处理特定对象识别和未知对象拒绝时.