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A Comparison of Four Data Selection Methods for Artificial Neural Networks and Support Vector Machines
2017
IFAC-PapersOnLine
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For classification, Support Vector Machines were used, while for the regression problems, Multi-Layer Perceptrons were employed. ...
For classification, Support Vector Machines were used, while for the regression problems, Multi-Layer Perceptrons were employed. ...
Although comparison between Multi Objective Genetic Algorithm (MOGA) designed models and Multi-Layer Perceptrons (MLPs) and Support Vector Machines (SVMs) will take place, the main objective of this paper ...
doi:10.1016/j.ifacol.2017.08.1577
fatcat:xm72bshvy5hsznr6fkq5yyi74q
Traffic Classification based on Adjustable Convex-hull Support Vector Machines
조절할 수 있는 볼록한 덮개 서포트 벡터 머신에 기반을 둔 트래픽 분류 방법
2012
Journal of the Korea Society of Computer and Information
조절할 수 있는 볼록한 덮개 서포트 벡터 머신에 기반을 둔 트래픽 분류 방법
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Support Vector Machine (SVM) is a useful classification tool which is able to overcome the traditional bottleneck. ...
However, the useful support vectors are only a small part of the whole data. If we can discard the useless vectors before training, we are able to save time and keep accuracy. ...
We called this adjustable convex hull. Figure 3 shows the concept of convex hull in the Support Vector Machines. ...
doi:10.9708/jksci.2012.17.3.067
fatcat:wpfkcq6cozbkbgk2hcfzhwxvey
Convex Hull-Based Feature Selection in Application to Classification of Wireless Capsule Endoscopic Images
[chapter]
2009
Lecture Notes in Computer Science
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The results obtained by means of the Vector Supported Convex Hull are compared with results produced by a Support Vector Machine with the radial basis function kernel. ...
In this paper we propose and examine a Vector Supported Convex Hull method for feature subset selection. ...
This work was supported by the Polish Ministry of Science and Higher Education grant no. 3263/B/T02/2008/35. ...
doi:10.1007/978-3-642-04697-1_62
fatcat:pha5cj6p2zahdicce6id325ksi
Performance of machine learning software to classify breast lesions using BI-RADS radiomic features on ultrasound images
2019
European Radiology Experimental
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Acknowledgements We acknowledge FAPESP for their financial support. ...
Decision tree (DT) [13] is a decision support tool that uses a tree-like graph and its possible consequences. It is a rule-based decision model. ...
The distance vector between the tumour contour and its convex hull is computed by a drawn of the convex hull of the tumour. ...
doi:10.1186/s41747-019-0112-7
pmid:31385114
pmcid:PMC6682836
fatcat:p2ixthacvrhunctl6awjdxmelm
Agent Collaborative Target Localization and Classification in Wireless Sensor Networks
2007
Sensors
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Desirable learning performance is guaranteed by combining support vectors and convex hull vectors. Fusion algorithms are designed to merge SVM classification decisions made from various modalities. ...
With the agent architecture, target classification is accomplished by distributed support vector machine (SVM). ...
Convex hull vector approach for distributed support vector machine learning The SV only algorithm is very intuitive and indeed effective in some cases, but not in all cases. ...
doi:10.3390/s7081359
fatcat:ewa3zuaw4fe4vcae63zyvgtc24
The Linear Separability Problem: Some Testing Methods
2006
IEEE Transactions on Neural Networks
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Index Terms-Class of separability, computational geometry, convex hull, Fisher linear discriminant, linear programming, linear separability, quadratic programming, simplex, support vector machine. research ...
Learning algorithms that use this concept to learn include neural networks (single layer perceptron and recursive deterministic perceptron), and kernel machines (support vector machines). ...
This is the case for the support vector machines (SVM). ...
doi:10.1109/tnn.2005.860871
pmid:16566462
fatcat:cfzzhgypozd5pkpxm5vdmdokuq
An Effective 3D Shape Descriptor for Object Recognition with RGB-D Sensors
2017
Sensors
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We extracted five features from contour-based images and five features from the 3D point cloud data. ...
These features are further concatenated into a 10-dimension vector as the representation of an object. ...
spin images and 3D bounding boxes used in [10] with linear support vector machine (LinSVM) and Gaussian kernel support vector machine (kSVM), respectively. ...
doi:10.3390/s17030451
pmid:28245553
pmcid:PMC5375737
fatcat:dvorrzsye5em7ltrmly4sn5z4u
A Real-Time Fire Detection Method from Video with Multifeature Fusion
2019
Computational Intelligence and Neuroscience
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Finally, we used support vector machine for training, completed the analysis of candidate fire images, and achieved automatic fire monitoring. ...
Then, we extracted features including spatial variability, shape variability, and area variability of the flame to improve the accuracy of recognition. ...
Final Verification of Candidate Fire Image Based on Support Vector Machine. ...
doi:10.1155/2019/1939171
pmid:31396269
pmcid:PMC6664547
fatcat:hddixu5ywnhrjeckpc6ikq4j7y
Fast Rule-Line Removal Using Integral Images and Support Vector Machines
2011
2011 International Conference on Document Analysis and Recognition
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We use an integral-image representation which allows fast computation of features and apply techniques for large scale Support Vector learning using a data selection strategy to sample a small subset of ...
Results on both constructed and real-world data sets show that the method is effective for rule-line removal. ...
ACKNOWLEDGMENT The partial support of this research by DARPA through BBN/DARPA Award HR0011-08-C-0004 under subcontract 9500009235, the US Government through NSF Award IIS-0812111 is gratefully acknowledged ...
doi:10.1109/icdar.2011.123
dblp:conf/icdar/KumarD11
fatcat:iygkcvh3kvexfak7yswpski3ca
Modeling of Hidden Markov in Ultrasound Image-Assisted Diagnosis
2021
Journal of Healthcare Engineering
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In addition, this study combines the convex hull algorithm for image processing, uses the improved vector method to repair, improves image recognizability, establishes a reliable feature extraction algorithm ...
Based on the hidden Markov model, this study processed the ultrasound images of pulmonary nodules to improve their diagnostic results. ...
Tsallis entropy and Shannon entropy as descriptive features and used the support vector machine (SVM) to classify lung nodules and nonnodular regions. ...
doi:10.1155/2021/5597591
fatcat:rlnedeme25ehxb6vsp7w6cd7iu
DataGrinder: Fast, Accurate, Fully non-Parametric Classification Approach Using 2D Convex Hulls
[article]
2015
arXiv
pre-print
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First, we thoroughly describe and prove our O(n) algorithm for finding the convex hull of a point set in 2D. ...
Our algorithm, proposes a way of combining 2D convex hulls in order to achieve high classification accuracy as well as scalability in the same time. ...
Support Vector Machine is a well researched problem with a complex structure. ...
arXiv:1511.03576v1
fatcat:lbfgfas36rarbk43274w63zxiy
From 3D Model Data to Semantics
2011
International Journal of Computer Science & Information Technology (IJCSIT)
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First, we focused on extracting invariant descriptors from the 3D models and analyzing them to efficient semantic annotation and to improve the retrieval accuracy. ...
The semantic-based 3D models retrieval systems have become necessary since the increase of 3D models databases. ...
Hou and al, in [10] Support Vector Machine (SVM) is used to cluster 3D models with respect to semantic information to organizing a database of shapes. ...
doi:10.5121/ijcsit.2011.3601
fatcat:7lsv5cdqtvfuxapiwsffais5m4
Hand Gesture Recognition Algorithm for Smart Cities based on Wireless Sensor
2017
International Journal of Online Engineering (iJOE)
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There are three main procedures; contour detection, convex extraction, and rule-based classification. The system can detect six different gestures on both hands in various orientations. ...
A vision-based algorithm is developed to detect and classify dynamic hand gestures in real time on the Raspberry Pi embedded platform. ...
Acknowledgement This research has been supported by Embedded System and IC Design research laboratory, Department of Electrical Engineering and Chulalongkorn Academic Advancement into Its 2nd Century Project ...
doi:10.3991/ijoe.v13i06.7022
fatcat:5q4c3g7u75abtb2fnu6n2237k4
Assessment of features technology
1991
Computer-Aided Design
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These fall broadly into the categories of interactive definition, automatic recognition/extraction, and design by features. ...
The paper reviews the major concepts and approaches that are in use in feature-based modeling. Several methodologies are prevalent for creating feature models and databases. ...
ACKNOWLEDGEMENTS The author gratefully acknowledges the financial support received from the Geometric Modeling Program of Computer-Aided Manufacturing International (CAM-I) (Contract # C-88-GM-01) and ...
doi:10.1016/0010-4485(91)90027-t
fatcat:qil6h7utm5d5nmt3nflhv6s2ku
An integrated segmentation and shape-based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT
2017
Medical Physics (Lancaster)
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The features thus identified were then combined with a support vector machine classifier and independently validated on a distinct test set comprising 67 patients. ...
This then enables the application of a gradient vector flow active contour (SEGvAC) model for nodule boundary extraction. ...
Acknowledgments Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award numbers 1U24CA199374-01, R01CA202752-01A1 R21CA179327 ...
doi:10.1002/mp.12208
pmid:28295386
pmcid:PMC5988352
fatcat:hzryvqg2dnhvdf2lixolkksusy
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