相关实验视频

Updated: Jun 16, 2025

Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

19.9K

深度交叉视图重建基于关联子空间的GAN,用于多视图转换

Jian-Xun Mi, Junchang He, Weisheng Li

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |August 19, 2024
    PubMed
    概括

    这项研究引入了一种新的图像转换框架,以改善不同相机类型的面部识别,如近红外 (NIR) 和热 (TH),克服不同照明条件带来的挑战.

    更多相关视频

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique04:48

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    380
    Real-time Video Projection in an MRI for Characterization of Neural Correlates Associated with Mirror Therapy for Phantom Limb Pain11:29

    Real-time Video Projection in an MRI for Characterization of Neural Correlates Associated with Mirror Therapy for Phantom Limb Pain

    Published on: April 20, 2019

    9.7K

    相关概念视频

    Cross Product01:25

    Cross Product

    The cross product is a fundamental concept in vector algebra that is a vector operation on two different vectors to obtain a third vector. Unlike the scalar product, the cross product results in a vector quantity perpendicular to both the original vectors.
    The magnitude of the cross product is obtained by multiplying the magnitude of both the vectors and the sine of the angle between them. This means that a larger angle between the vectors will lead to a greater magnitude of the cross product.
    237
    Deconvolution01:20

    Deconvolution

    Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
    Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
    143
    Transformation of Plane Strain01:12

    Transformation of Plane Strain

    When analyzing elongated structures like bars subjected to uniformly distributed loads, it is essential to understand the transformation of plane strain when coordinate axes are rotated. This transformation helps to assess how material deformation characteristics vary with orientation, which is crucial in materials science and structural engineering.
    Under plane strain conditions, typical for members where one dimension significantly exceeds the others, deformations and resultant strains are...
    159
    Deformations in a Transverse Cross Section01:21

    Deformations in a Transverse Cross Section

    When a material is subjected to uniaxial stress, it elongates or contracts in the direction of the applied force, and also undergoes changes in the perpendicular directions. This behavior is crucial for understanding how materials behave under stress and is governed by mechanical properties such as Poisson's ratio v, which measures the ratio of transverse strain to axial strain.
    As the material stretches, it expands or contracts in orthogonal directions to the load. This phenomenon varies...
    180
    Collisions in Multiple Dimensions: Introduction01:05

    Collisions in Multiple Dimensions: Introduction

    It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
    4.9K
    Depth Perception and Spatial Vision01:15

    Depth Perception and Spatial Vision

    Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
    612