A Robust and Efficient Curve Skeletonization Algorithm for Tree-Like Objects Using Minimum Cost Paths [0.03%]
一种基于最小代价路径的稳健和高效的曲线骨干算法用于树状对象
Dakai Jin,Krishna S Iyer,Cheng Chen et al.
Dakai Jin et al.
Conventional curve skeletonization algorithms using the principle of Blum's transform, often, produce unwanted spurious branches due to boundary irregularities, digital effects, and other artifacts. This paper presents a new robust and effi...
Towards a real-time interface between a biomimetic model of sensorimotor cortex and a robotic arm [0.03%]
大脑感觉运动皮层生物仿真模型与机器人手臂之间的实时接口研究
Salvador Dura-Bernal,George L Chadderdon,Samuel A Neymotin et al.
Salvador Dura-Bernal et al.
Brain-machine interfaces can greatly improve the performance of prosthetics. Utilizing biomimetic neuronal modeling in brain machine interfaces (BMI) offers the possibility of providing naturalistic motor-control algorithms for control of a...
Jeffrey M Girard,Jeffrey F Cohn,Fernando De la Torre
Jeffrey M Girard
Both the occurrence and intensity of facial expressions are critical to what the face reveals. While much progress has been made towards the automatic detection of facial expression occurrence, controversy exists about how to estimate expre...
Hamse Y Mussa,John B O Mitchell,Avid M Afzal
Hamse Y Mussa
Pattern classification methods assign an object to one of several predefined classes/categories based on features extracted from observed attributes of the object (pattern). When L discriminatory features for the pattern can be accurately d...
Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition [0.03%]
基于无监督聚类和有限的手工标记的半自动地面实况生成：手写字符识别中的应用
Szilárd Vajda,Yves Rangoni,Hubert Cecotti
Szilárd Vajda
For training supervised classifiers to recognize different patterns, large data collections with accurate labels are necessary. In this paper, we propose a generic, semi-automatic labeling technique for large handwritten character collectio...
Esra Ataer-Cansizoglu,Murat Akcakaya,Umut Orhan et al.
Esra Ataer-Cansizoglu et al.
Nonlinear dimensionality reduction is essential for the analysis and the interpretation of high dimensional data sets. In this manuscript, we propose a distance order preserving manifold learning algorithm that extends the basic mean-square...
Hu Huang,Akif Burak Tosun,Jia Guo et al.
Hu Huang et al.
Methods for extracting quantitative information regarding nuclear morphology from histopathology images have been long used to aid pathologists in determining the degree of differentiation in numerous malignancies. Most methods currently in...
Coupled dimensionality reduction and classification for supervised and semi-supervised multilabel learning [0.03%]
基于监督和半监督多标签学习的耦合降维与分类算法研究
Mehmet Gönen
Mehmet Gönen
Coupled training of dimensionality reduction and classification is proposed previously to improve the prediction performance for single-label problems. Following this line of research, in this paper, we first introduce a novel Bayesian meth...
Xiaodong Yang,Yingli Tian
Xiaodong Yang
In this paper, we propose a texture representation framework to map local texture patches into a low-dimensional texture subspace. In natural texture images, textons are entangled with multiple factors, such as rotation, scaling, viewpoint ...
A New Distance Measure Based on Generalized Image Normalized Cross-Correlation for Robust Video Tracking and Image Recognition [0.03%]
一种基于广义图像归一化互相关的新型距离度量用于鲁棒视频跟踪和图像识别
Arie Nakhmani,Allen Tannenbaum
Arie Nakhmani
We propose two novel distance measures, normalized between 0 and 1, and based on normalized cross-correlation for image matching. These distance measures explicitly utilize the fact that for natural images there is a high correlation betwee...