代码搜索:Gradient

找到约 2,951 项符合「Gradient」的源代码

代码结果 2,951
www.eeworm.com/read/349902/10786680

tff grb.tff

# TextFileFormat (leave this tag as magic token!) # BVQX file format for *.GRB files (GRadient and B-values information) # GRB FileVersions supported: 1 # # Version: v0.6f # Build: 7062612
www.eeworm.com/read/275385/10820228

c pcg.c

/* * pcg.c -- function for Preconditioned Conjugate Gradient solution * of weighted least-squares phase-unwrapping problem */ #include #include #include "solncos
www.eeworm.com/read/417657/10981205

m~ findseamimg.m~

function SeamImg=findSeamImg(x) % FINDSEAMIMG finds the seam map from which the optimal (vertical running) % seam can be calculated. Input is gradient image found from findEnergy.m. % % The index
www.eeworm.com/read/417657/10981212

m findseamimg.m

function SeamImg=findSeamImg(x) % FINDSEAMIMG finds the seam map from which the optimal (vertical running) % seam can be calculated. Input is gradient image found from findEnergy.m. % % The index
www.eeworm.com/read/466394/7034626

m emshift.m

function [xt,Vt]=EMShift(im0,xt,V,histO,K,beta,varargin) %Calculate gradient step to maximize similarity between the target %and the object histogram - Bhattacharayya coefficient %The step is in bo
www.eeworm.com/read/449077/7518931

m findseamimg.m

function SeamImg=findSeamImg(x) % FINDSEAMIMG finds the seam map from which the optimal (vertical running) % seam can be calculated. Input is gradient image found from findEnergy.m. % % The index
www.eeworm.com/read/197354/8002306

clw gradienttxt.clw

; CLW file contains information for the MFC ClassWizard [General Info] Version=1 LastClass=CAboutDlg LastTemplate=CDialog NewFileInclude1=#include "stdafx.h" NewFileInclude2=#include "Gradient
www.eeworm.com/read/397967/8012499

m findseamimg.m

function SeamImg=findSeamImg(x) % FINDSEAMIMG finds the seam map from which the optimal (vertical running) % seam can be calculated. Input is gradient image found from findEnergy.m. % % The index
www.eeworm.com/read/143706/12849510

m demolgd1.m

%DEMOLGD1 Demonstrate simple MLP optimisation with on-line gradient descent % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
www.eeworm.com/read/315227/13548535

f90 dsrc2c.f90

SUBROUTINE JCG (NN,IA,JA,A,RHS,U,IWKSP,NW,WKSP,IPARM,RPARM,IERR) ! ! ITPACK 2C MAIN SUBROUTINE JCG (JACOBI CONJUGATE GRADIENT) ! EACH OF THE MAIN SUBROUTINES: !