Filters








13,196 Hits in 5.4 sec

Clustering pair-wise dissimilarity data into partially ordered sets

Jinze Liu, Qi Zhang, Wei Wang, Leonard McMillan, Jan Prins
2006 Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06  
In fact, only special types of dissimilarity matrices can be exactly preserved by previous clustering methods. We model ontologies as a partially ordered set (poset) over the subset relation.  ...  Ontologies are closely related to clustering hierarchies, and in this article we explore this relationship in depth.  ...  From an application standpoint, the goal of our paper is to derive plausible ontology-like categorizations of objects from a pairwise dissimilarity matrix via a clustering algorithm.  ... 
doi:10.1145/1150402.1150480 dblp:conf/kdd/LiuZWMP06 fatcat:oxnbaqhuavbt7khe7gpbwu5cpi

Extracting the abstraction pyramid from complex networks

Chia-Ying Cheng, Yuh-Jyh Hu
2010 BMC Bioinformatics  
Pyramabs was designed to interpret a complex network through a disclosure of a pyramid of abstractions.  ...  from a complex system of interacting objects.  ...  Sales-Pardo for providing the datasets and the source code for the tools used in the experiments. This work was partially supported by National Science Council (NSC) of Taiwan, NSC 98-2221-E-009-150.  ... 
doi:10.1186/1471-2105-11-411 pmid:20682075 pmcid:PMC2921411 fatcat:jtvdso2vonefjnugva2hcewwd4

Recent progress in semantic image segmentation

Xiaolong Liu, Zhidong Deng, Yuhan Yang
2018 Artificial Intelligence Review  
Semantic image segmentation, which becomes one of the key applications in image processing and computer vision domain, has been used in multiple domains such as medical area and intelligent transportation  ...  Lots of benchmark datasets are released for researchers to verify their algorithms. Semantic segmentation has been studied for many years.  ...  Introduction Semantic image segmentation, also called pixel-level classification, is the task of clustering parts of image together which belong to the same object class (Thoma 2016) .  ... 
doi:10.1007/s10462-018-9641-3 fatcat:refuxyn4n5eatfeb6npgrichza

Stacked spatial-pyramid kernel: An object-class recognition method to combine scores from random trees

N. Larios, J. Lin, M. Zhang, D. Lytle, A. Moldenke, L. Shapiro, T. Dietterich
2011 2011 IEEE Workshop on Applications of Computer Vision (WACV)  
The combination of local features, complementary feature types, and relative position information has been successfully applied to many object-class recognition tasks.  ...  This classification method is applied to the task of automated insect-species identification for biomonitoring purposes.  ...  The accumulation of discriminative information in the form of scores is the main difference between our method and the original spatial-pyramid kernel SVM method [10] , which only accumulates cluster  ... 
doi:10.1109/wacv.2011.5711522 dblp:conf/wacv/DelgadoLZLMSD11 fatcat:6dxxc3imxvhbvcbjhnzpnmnhsq

Motion Estimation for Video Bandwidth Compression Using a Heterogeneous Pyramid Image Processing Architecture

Graham R. Nudd, Simon Clippingdale, R. M. Howarth, Tim J. Atherton, Nick D. Francis, G. John Vaudin, D. Walton
1988 IAPR International Workshop on Machine Vision Applications  
This paper describes the mapping of the block motion estimator on to the lower levels of the Wamick Pyramid Machine (WPM), a heterogeneous pyramid architecture for parallel image processing I understanding  ...  reference to a neighbourhood in the previous frame.  ...  Somewhat more limited in terms of permissible types of object and motion are the feature correspondence methods.  ... 
dblp:conf/mva/NuddCHAFVW88 fatcat:t2ho3h547fhspp5p5i77jwtv24

An extended version of the k-means method for overlapping clustering

Guillaume Cleuziou
2008 Pattern Recognition (ICPR), Proceedings of the International Conference on  
We show that the problem of finding a suitable coverage of data by overlapping clusters is not a trivial task.  ...  We propose a new objective criterion and the associated algorithm OKM that generalizes the k-means algorithm.  ...  Acknowledgments The research reported in this paper is partially funded by the French National Research Agency ANR (project GD2GS).  ... 
doi:10.1109/icpr.2008.4761079 dblp:conf/icpr/Cleuziou08 fatcat:sylgheldjnbfrkpklayd2bne6y

Optical tug-of-war tweezers: shaping light for dynamic control of bacterial cells (Invited Paper)

Joshua Lamstein Joshua Lamstein, Anna Bezryadina Anna Bezryadina, Daryl Preece Daryl Preece, Joseph C. Chen Joseph C. Chen, and Zhigang Chen and Zhigang Chen
2017 Chinese Optics Letters (COL)  
With appropriate beam shaping, the dual tug-of-war tweezers effectively hold and stretch elongated biological objects of different sizes, and the triangular tug-of-war tweezers with threefold rotational  ...  symmetry steadily hold asymmetric objects in the plane of observation and exert stretching forces along three directions.  ...  This work was supported in part by the NIH, NSF, and ASOFR. † These authors are contributed equally to this work.  ... 
doi:10.3788/col201715.030010 fatcat:nmipipz4o5evzhdps5zeaskm7a

Synapse classification and localization in Electron Micrographs

Vignesh Jagadeesh, James Anderson, Bryan Jones, Robert Marc, Steven Fisher, B.S. Manjunath
2014 Pattern Recognition Letters  
Experimental results on images acquired from a mammalian retinal tissue compare favorably with state of the art descriptors used for object detection.  ...  Classification and detection of biological structures in Electron Micrographs (EM) is a relatively new large scale image analysis problem.  ...  Strong Biological Priors: Object detection refers to the problem of identifying the spatial location of an object of interest in images.  ... 
doi:10.1016/j.patrec.2013.06.001 fatcat:2xd3dtpjmfh75bt4edvwzg5z7q

Low-level global features for vision-based localizations

Sven Eberhardt, Christoph Zetzsche
2013 Deutsche Jahrestagung für Künstliche Intelligenz  
Application of several biologically inspired algorithms to various test sets reveals that simple, globally pooled features outperform the complex vision models used for object recognition, if tested on  ...  Vision-based self-localization is the ability to derive one's own location from visual input only without knowledge of a previous position or idiothetic information.  ...  The response vectors are clustered into 128 textons and each pixel is assigned the cluster with the least square distance to its response vector.  ... 
dblp:conf/ki/EberhardtZ13 fatcat:5p32totfczflxb3zishbwgppty

Epithelial Area Detection in Cytokeratin Microscopic Images Using MSER Segmentation in an Anisotropic Pyramid [chapter]

Cristian Smochina, Radu Rogojanu, Vasile Manta, Walter Kropatsch
2011 Lecture Notes in Computer Science  
The objective of semantic segmentation in microscopic images is to extract the cellular, nuclear or tissue components.  ...  The evaluation of the proposed method is made by comparing the results with ground-truth segmentations.  ...  which the objects of interest have the features considered in designing this method.  ... 
doi:10.1007/978-3-642-24855-9_28 fatcat:prt3x4qjcba5ff5bynrbqdoa4y

Beyond sliding windows: Object localization by efficient subwindow search

Christoph H. Lampert, Matthew B. Blaschko, Thomas Hofmann
2008 2008 IEEE Conference on Computer Vision and Pattern Recognition  
It converges to a globally optimal solution typically in sublinear time. We show how our method is applicable to different object detection and retrieval scenarios.  ...  The achieved speedup allows the use of classifiers for localization that formerly were considered too slow for this task, such as SVMs with a spatial pyramid kernel or nearest neighbor classifiers based  ...  Acknowledgments This work was funded in part by the EC project CLASS, IST 027978. The second author is supported by a Marie Curie fellowship under the EC project PerAct, EST 504321.  ... 
doi:10.1109/cvpr.2008.4587586 dblp:conf/cvpr/LampertBH08 fatcat:chnpncmuujdzxf4ed25ex6y6le

A multi-focus image fusion method via region mosaicking on Laplacian pyramids

Liang Kou, Liguo Zhang, Kejia Zhang, Jianguo Sun, Qilong Han, Zilong Jin, A Lenin Fred
2018 PLoS ONE  
In addition, RMLP is insensitive to noise and can reduces the color distortion of the fused images on two datasets. (2018) A multi-focus image fusion method via region mosaicking on Laplacian pyramids.  ...  First, the Sum-Modified-Laplacian is applied to measure the focus of multi-focus images. Then the density-based region growing algorithm is utilized to segment the focused region mask of each image.  ...  The two datasets belong in the typical applications of forensic and biological fields.  ... 
doi:10.1371/journal.pone.0191085 pmid:29771912 pmcid:PMC5957432 fatcat:6q66f6zf3bgrrj6dcdygjqnbbu

Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach

Humayun Irshad, Sepehr Jalali, Ludovic Roux, Daniel Racoceanu, GillesLe Naour, LimJoo Hwee, Frédérique Capron
2013 Journal of Pathology Informatics  
We also evaluate the performance of the proposed framework using the modified biologically inspired model of HMAX and compare the results with other feature extraction methods such as dense SIFT.  ...  In future work, instead of regions, we intend to compute features on the results of mitosis contour segmentation and use them to improve detection and classification rate.  ...  ACKNOWLEDGMENT This work is supported by the French National Research Agency (ANR), project MICO under reference ANR-10-TECS-015.  ... 
doi:10.4103/2153-3539.109870 pmid:23766934 pmcid:PMC3678748 fatcat:46ih5bvxcrby5brv734hm2kz6u

Introduction to the Bag of Features Paradigm for Image Classification and Retrieval [article]

Stephen O'Hara, Bruce A. Draper
2011 arXiv   pre-print
Among the more fundamental challenges are how and whether BoF methods can contribute to localizing objects in complex images, or to associating high-level semantics with natural images.  ...  The past decade has seen the growing popularity of Bag of Features (BoF) approaches to many computer vision tasks, including image classification, video search, robot localization, and texture recognition  ...  Wrapping up our discussion of works relating to BoF image classification are biologically inspired methods for scene classification.  ... 
arXiv:1101.3354v1 fatcat:bmiomdpje5fhlfrzrlhhhpvt3u

Stacked Predictive Sparse Decomposition for Classification of Histology Sections

Hang Chang, Yin Zhou, Alexander Borowsky, Kenneth Barner, Paul Spellman, Bahram Parvin
2014 International Journal of Computer Vision  
Furthermore, the study of these indices, constructed from each whole slide image in a large cohort, has the potential to provide predictive models of clinical outcome.  ...  The learned representation is then fed into the spatial pyramid matching framework with a linear support vector machine classifier.  ...  Acknowledgments This work was supported by National Institute of Health (NIH) U24 CA1437991 and NIH R01 CA140663 carried out at Lawrence Berkeley National Laboratory under Contract No.  ... 
doi:10.1007/s11263-014-0790-9 pmid:27721567 pmcid:PMC5051579 fatcat:m2uwfsks6nd47kfiy6xcfhm22m
« Previous Showing results 1 — 15 out of 13,196 results