An ideal anti‐counterfeiting label not only needs to be unclonable and accurate but also
must consider cost and efficiency. But the traditional physical unclonable function (PUF) …

Deep learning based action recognition methods require large amount of labelled training
data. However, labelling large-scale video data is time consuming and tedious. In this paper …

In this work, we propose a novel architecture style recognition model by introducing
blocklets that capture the morphological characteristics of buildings. First, we decompose a …

Considering human can learn new object successfully from just one sample, one-shot
learning, where each visual class just has one labeled sample for training, has attracted …

Object recognition is one of the most important tasks in computer vision domain and it has
been extensively applied in many areas during the last three decades. In this paper, a …

The goal of image style transfer is to render an image guided by a style reference while
maintaining the original content. Existing image-guided methods rely on specific style …

Understanding how the structure of materials affects their properties is a cornerstone of
materials science and engineering. However, traditional methods have struggled to …

传统的Kendall 形状空间理论仅适用于相似变换, 然而成像过程中目标发生的几何变形在更多
情形时应该用仿射变换来刻画. 基于Grassmann 流形理论, 本文分析了仿射不变形状空间的非 …

Computer vision has been extensively adopted in many domains during the last three
decades. One of the main goals of computer vision applications is to recognize objects …

Deep learning has yielded remarkable outcomes in various domains. However, the
challenge of requiring large-scale labeled samples still persists in deep learning. Thus, data …