Inside This Book (learn more) First Sentence: Suppose one is given a set V of objects, called vectors. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more) elementary alternating tensors, elementary matrix correspo
Descr iption Tutorial on structure tensors. Normally associated with image processing and structure inference, this code provides a completely encapsulated package to explain and demonstrate the use of structure tensors. playshow structureTensorDemo
1. Physics in Flat Spacetime: Geometric Viewpoint 1.1 Overview 1.2 Foundational Concepts 1.3 Tensor Algebra Without a Coordinate System 1.4 Particle Kinetics and Lorentz Force Without a Reference Frame 1.5 Component Representation of Tensor Algebra
Abstract—This paper introduces a multilinear principal com- ponent analysis (MPCA) framework for tensor object feature extraction. Objects of interest in many computer vision and pattern recognition applications, such as 2-D/3-D images and video seq
This introductory textbook presents the modern signal processing concepts used in computer vision and image analysis in a systematic and mathematically coherent way. For the first time in a textbook on image processing, single direction, group direc
In this paper, we augment existing techniques for simulating flexible objects to include models for crack initiation and propagation in three-dimensional volumes. By analyzing the stress tensors computed over a finite element model, the simulation d
We discuss a multilinear generalization of the singular value decomposition. There is a strong analogy between several properties of the matrix and the higher-order tensor decomposition; uniqueness, link with the matrix eigenvalue decomposition, fir
John M. Lee三本经典中的第二本，主要讲光滑流形，是自学流形以及查阅资料绝佳选择，此版为2012新版，涵盖tangent and cotangent bundles，vector bundles, differential forms,tensors,De Rham Cohomology，Exponential Map，,流形的定向和流行上的微积分等。
Covariance matrices have recently been a popular choice for versatile tasks like recognition and tracking due to their powerful properties as local descr iptor and their low computational demands. This paper outlines similarities of covariance matri
This book is about tensor analysis. It consists of 169 pages. The language and method used in presenting the ideas and techniques of tensors make it very suitable as a textbook or as a reference for an introductory course on tensor algebra and calcu
Book Descr iption This book of projects highlights how TensorFlow can be used in different scenarios - this includes projects for training models, machine learning, deep learning, and working with various neural networks. Each project provides excit
This survey provides an overview of higher-order tensor decompositions, their applications, and available software. A tensor is a multidimensional or N-way array. Decompositions of higher-order tensors (i.e., N-way arrays with N ≥ 3) have applicatio
在调整loss计算的时候遇到了TypeError: only integer tensors of a single element can be converted to an index这个问题，原来的计算公式为：
self.loss_D = (self.loss_D_fake + self.loss_D_real) * 0.5
调整后的公式为：
# train.lcf[train.lcfCountD]为修正系数
self.loss_D = (self.loss_D_fake + self
