Cross-Domain Visual Matching,即跨域视觉匹配.所谓跨域,指的是数据的分布不一样,简单点说,就是两种数据「看起来」不像.如下图中,(a)一般的正面照片和各种背景角度下拍摄的照片:(b)摄像头不同角度下拍到的照片:(c)年轻和年老时的人脸照:(d)证件照和草图风格的人脸照,这些图像都存在对应关系,但由于它们属于不同的域,因此必须针对不同的域采用不同的特征提取方法,之后再做特征匹配.这篇论文提出用一种通用的相似模型来匹配两个域之间的特征,并将其和特征提取流程融合在一起,统一…

# by movie on 2019/12/18 import matplotlib.pyplot as plt import numpy as np from skimage import measure import cv2 # import the necessary packages def mse(imageA, imageB): # the 'Mean Squared Error' between the two images is the # sum of the squared…

1. https://blog.csdn.net/m0_37676632/article/details/68936157 2. https://www.cnblogs.com/pinard/p/6208966.html…

Algorithm: Refrence from one ICML15 paper: Word Mover's Distance. 1. First use Google's word2vec tool to get distributed word representing aka. word vectors. 2. Then use earth mover's distance as similarity measure metric. 3. Solve the EMD problem as…

Basis(基础): SSE(Sum of Squared Error, 平方误差和) SAE(Sum of Absolute Error, 绝对误差和) SRE(Sum of Relative Error, 相对误差和) MSE(Mean Squared Error, 均方误差) RMSE(Root Mean Squared Error, 均方根误差) RRSE(Root Relative Squared Error, 相对平方根误差) MAE(Mean Absolute Error, 平均绝…

转自:https://iksinc.wordpress.com/tag/continuous-bag-of-words-cbow/ 清晰易懂. Vector space model is well known in information retrieval where each document is represented as a vector. The vector components represent weights or importance of each word in th…

This article come from HEREARS-L1: Learning Tuesday 10:30–12:30; Oral Session; Room: Leonard de Vinci 10:30  ARS-L1.1—GROUP STRUCTURED DIRTY DICTIONARY LEARNING FOR CLASSIFICATION Yuanming Suo, Minh Dao, Trac Tran, Johns Hopkins University, USA; Hojj…

This list is not exhaustive - help expand it! Social Tagging Systems Research Group Source Year Obtained Availability Contact References CiteULike Oversity Ltd. Primary Daily Snapshots Via Download after Email (link) Richard Cameron   Bibsonomy KDE P…

转自: [基础]常用的机器学习&数据挖掘知识点 Basis(基础): MSE(Mean Square Error 均方误差),LMS(LeastMean Square 最小均方),LSM(Least Square Methods 最小二乘法),MLE(MaximumLikelihood Estimation最大似然估计),QP(Quadratic Programming 二次规划), CP(Conditional Probability条件概率),JP(Joint Probability 联合概…

Basis(基础): MSE(Mean Square Error 均方误差),LMS(LeastMean Square 最小均方),LSM(Least Square Methods 最小二乘法),MLE(MaximumLikelihood Estimation最大似然估计),QP(Quadratic Programming 二次规划), CP(Conditional Probability条件概率),JP(Joint Probability 联合概率),MP(Marginal Probabili…