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A New Approach of Dynamic Clustering Based on Particle Swarm Optimization and Application in Image Segmentation
2017
Computing and informatics
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The improved PSO is then combined with the well-known data clustering k-means algorithm for dynamic clustering problem where the number of clusters has not yet been known. ...
This paper presents a new approach of dynamic clustering based on improved Particle Swarm Optimization (PSO) and which is applied to image segmentation (called DCPSONS). ...
There are many methods for image segmentation in the literature [28, 29] , of which one of the popular method is to use a clustering algorithm (such as k-means). ...
doi:10.4149/cai_2017_3_637
fatcat:5e7hov3lrfeqjfecyjeelbului
IDENTIFICATION OF PATCHOULI PLANTS USING LANDSAT-8 SATELLITE IMAGERY AND IMPROVED K-MEANS METHOD
2016
Journal of Enviromental Engineering and Sustainable Technology
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The test results also show that the use of the Improved K-Means on the Landsat-8 image has not been able to recognize the difference patchouli plants with other crops due to the limited resolution of imagery ...
This study performed the identification of patchouli plant through Landsat-8 satellite imagery and Improved K-Means method. ...
This study combine the KK-means clustering segmentation algorithm and mathematical morphology. The results show that the algorithm can separate between the fish image and the complex backgrounds. ...
doi:10.21776/ub.jeest.2016.003.02.1
fatcat:3eogqdguvrb5hpk35z74zopp7y
A Feature Learning and Object Recognition Framework for Underwater Fish Images
[article]
2016
arXiv
pre-print
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For the classifier, an unsupervised clustering approach generates a binary class hierarchy, where each node is a classifier. ...
Toward this end, we propose an underwater fish recognition framework that consists of a fully unsupervised feature learning technique and an error-resilient classifier. ...
Object segmentation mask for each fish image is provided along with the dataset. ...
arXiv:1603.01696v1
fatcat:6tzaud6bjbbqldsxkgeq234mm4
Improved Artificial Bee Colony Using Sine-Cosine Algorithm for Multi-level Thresholding Image Segmentation
2020
IEEE Access
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Multilevel-thresholding is an efficient method used in image segmentation. ...
This paper presents a hybrid meta-heuristic approach for multi-level thresholding image segmentation by integrating both the artificial bee colony (ABC) algorithm and the sine-cosine algorithm (SCA). ...
The FA was proposed in [35] for MTS to improve the performance of the K-means algorithm. The results showed high performance and good segmentation result for the proposed method. ...
doi:10.1109/access.2020.2971249
fatcat:psy7dvisdrebxmzwjwo536adqe
Integration of evolutionary computation algorithms and new AUTO-TLBO technique in the speaker clustering stage for speaker diarization of broadcast news
2017
EURASIP Journal on Audio, Speech, and Music Processing
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grouping of speakers' segments. ...
Clustering validity indexes, such as Within-Class Distance (WCD) index, Davies and Bouldin (DB) index, and Contemporary Document (CD) index, is also used in order to make a correction for each possible ...
Indeed, obtaining GMM for a segment is done by mean adapting the UBM for the feature vectors of the concerned segment. ...
doi:10.1186/s13636-017-0117-1
fatcat:htbtt6oqnrdi5g5xliioqkl66i
Super-resolution Imaging Reveals 3D Structure and Organizing Mechanism of Accessible Chromatin
[article]
2019
bioRxiv
pre-print
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Access to cis-regulatory elements packaged in chromatin is essential for directing gene expression and cell viability. ...
We found that active chromosomal segments are organized into spatially-segregated accessible chromatin domains (ACDs). ...
We also thank Deepika Walpita and Kathy Schaefer with assistance for FACS experiments, Damien Alcor for Airyscan Imaging and Melanie Radcliff for assistance. ...
doi:10.1101/678649
fatcat:isascfdol5cbbmq46bnyvm7hii
Figure-ground organization based on three-dimensional symmetry
2016
Journal of Electronic Imaging (JEI)
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We tested our approach on a corpus of 180 images collected indoors with a stereo camera system. K -means clustering was used as a baseline for comparison. ...
No general purpose approach is known for solving 3-D symmetry correspondence in two-dimensional (2-D) camera images, because few invariants exist. ...
We would like to thank the reviewers for their helpful feedback, and Vikrant Satheesh for annotating the testing corpus. ...
doi:10.1117/1.jei.25.6.061606
fatcat:zsgk2t6fjjcbdlyo6giy6xcmim
Joint-Space Kinematic Control of a Bionic Continuum Manipulator in Real-time by using Hybrid Approach
2022
IEEE Access
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This research is partly funded by Indo French Centre for the Promotion of Advanced Research (IFCPAR), under DST (India) and CNRS (France) Collaboration for the project "Modelling and control of mobile ...
The work in [33] is extended in [34] to formulate an adaptive NN model for improved trajectory tracking. ...
P and 𝐊𝐊 I are tuned by minimising the total mean square error (MSE) of the system. ...
doi:10.1109/access.2022.3171236
fatcat:2osulv3edfhczl6osdmhvcoooe
Learning invariant structure for object identification by using graph methods
2011
Computer Vision and Image Understanding
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Practically, we depend on spectral graph analysis of a hierarchical description of an image to construct a feature vector of fixed dimension. ...
Acknowledgements This work was supported by EPSRC Grant EP/D05429X/1, Fundamental Research Funds for the Cental Universities and Open Projects of National Laboratory of Pattern Recognition. ...
The difference this conditioning matrix makes can be witnessed in Fig. 2 , where improved segmentations clearly result. ...
doi:10.1016/j.cviu.2010.12.016
fatcat:qhdoq4xrkrhllon3hd6ep2ttju
Light microscopy applications in systems biology: opportunities and challenges
2013
Cell Communication and Signaling
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Ilastik is an open-source tool based on user defined examples that train a machine-learning algorithm for identifying pixels of an image that belong to a class of interest [93, 136] . ...
However, in contrast to classical tracking and cell lineage identification algorithms, improved algorithms that consider the entire image sequence, and prior knowledge (e.g., about mitosis and apoptosis ...
CT prepared the tables of the manuscript, AS focused on the machine learning part, AB on microscopes, and KK helped to improve the review of workflow systems and databases. ...
doi:10.1186/1478-811x-11-24
pmid:23578051
pmcid:PMC3627909
fatcat:xfq3tvkb2reg7heojzoj2omb4e
A skeletal measure of 2D shape similarity
2004
Computer Vision and Image Understanding
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We illustrate how the new shapemeasure can be used for the purposes of clustering shock-trees of the same shape class. ...
Details of the clustering algorithm are outside the scope of this paper. However, the method uses an iterative log-likelihood algorithm to identify the pairwise clusters via matrix factorization. ...
This means that very short boundary segments generate very long skeleton branches. ...
doi:10.1016/j.cviu.2004.03.006
fatcat:pakmyur5jfcanpxlssz3hg6rgm
A skeletal measure of 2D shape similarity
2004
Computer Vision and Image Understanding
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We illustrate how the new shapemeasure can be used for the purposes of clustering shock-trees of the same shape class. ...
Details of the clustering algorithm are outside the scope of this paper. However, the method uses an iterative log-likelihood algorithm to identify the pairwise clusters via matrix factorization. ...
This means that very short boundary segments generate very long skeleton branches. ...
doi:10.1016/s1077-3142(04)00037-2
fatcat:oci2xhnqdncedopzctc7aqggnm
Analysis and synthesis of 3D shape families via deep-learned generative models of surfaces
2015
Computer graphics forum (Print)
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We provide qualitative and quantitative evaluations of our method for shape correspondence, segmentation, fine-grained classification and synthesis. ...
Finally, it can be also coupled with the probabilistic deformation model to further improve shape correspondence. ...
We thank Qi-xing Huang and Vladimir Kim for sharing data from their methods. We thank Siddhartha Chaudhuri and anonymous reviewers for valuable comments. ...
doi:10.1111/cgf.12694
fatcat:6hmtn4da6zc4rf2mnemye3v4ie
A Skeletal Measure of 2D Shape Similarity
[chapter]
2001
Lecture Notes in Computer Science
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We illustrate how the new shapemeasure can be used for the purposes of clustering shock-trees of the same shape class. ...
Details of the clustering algorithm are outside the scope of this paper. However, the method uses an iterative log-likelihood algorithm to identify the pairwise clusters via matrix factorization. ...
This means that very short boundary segments generate very long skeleton branches. ...
doi:10.1007/3-540-45129-3_23
fatcat:txclelvglbakzprklezdb3nlbu
D3.6: 2nd Design Guidelines for Open Sensor fabrication
2018
Zenodo
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The current report is the second version of the design guidelines for the hackAIR open sensor fabrication that describes the implementation details of three open hardware solutions along with an initial ...
version of user guidelines for the construction of each one. ...
[30] 5.5.6 Clustering (The Otsu Method) In image processing, segmentation is often the first step to pre-process images to extract objects of interest for further analysis. ...
doi:10.5281/zenodo.2252161
fatcat:ypobqwoa3jf7jd4z7rn4hrba7m
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