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A Comparison of Four Data Selection Methods for Artificial Neural Networks and Support Vector Machines

H. Khosravani, A. Ruano, P.M. Ferreira
2017 IFAC-PapersOnLine  
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

Zhibin Yu, Yong-Do Choi, Gi-Beom Kil, Sung-Ho Kim
2012 Journal of the Korea Society of Computer and Information  
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]

Piotr Szczypiński, Artur Klepaczko
2009 Lecture Notes in Computer Science  
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

Eduardo Fleury, Karem Marcomini
2019 European Radiology Experimental  
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

Xue Wang, Dao-wei Bi, Liang Ding, Sheng Wang
2007 Sensors  
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

D. Elizondo
2006 IEEE Transactions on Neural Networks  
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

Zhong Liu, Changchen Zhao, Xingming Wu, Weihai Chen
2017 Sensors  
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

Faming Gong, Chuantao Li, Wenjuan Gong, Xin Li, Xiangbing Yuan, Yuhui Ma, Tao Song
2019 Computational Intelligence and Neuroscience  
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

Jayant Kumar, David Doermann
2011 2011 International Conference on Document Analysis and Recognition  
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

Liping Shao, Zubang Zhou, Hongmei Wu, Jinrong Ni, Shulan Li, Zhihan Lv
2021 Journal of Healthcare Engineering  
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]

Mohammad Khabbaz
2015 arXiv   pre-print
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

My Abdellah Kassimi, Omar El beqqali
2011 International Journal of Computer Science & Information Technology (IJCSIT)  
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

Thittaporn Ganokratanaa, Suree Pumrin
2017 International Journal of Online Engineering (iJOE)  
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

J.J. Shah
1991 Computer-Aided Design  
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

Mehdi Alilou, Niha Beig, Mahdi Orooji, Prabhakar Rajiah, Vamsidhar Velcheti, Sagar Rakshit, Niyoti Reddy, Michael Yang, Frank Jacono, Robert C. Gilkeson, Philip Linden, Anant Madabhushi
2017 Medical Physics (Lancaster)  
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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