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Model-Based Object Recognition from a Complex Binary Imagery Using Genetic Algorithm [chapter]

Samarjit Chakraborty, Sudipta De, Kalyanmoy Deb
1999 Lecture Notes in Computer Science  
This paper describes a technique for model-based object recognition in a noisy and cluttered environment, by extending the work presented in an earlier study by the authors.  ...  A special form of template matching is used to deal with the noisy environment, where the templates are generated on-line by a Genetic Algorithm.  ...  Object recognition in a complex image using GA has also been attempted 26].  ... 
doi:10.1007/10704703_12 fatcat:twdxsfwdebf7vkjo54uti4j3ku

Satellite Imagery Classification Based On Deep Convolution Network

Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu
2016 Zenodo  
Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database.  ...  Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform  ...  ACKNOWLEDGMENT The authors thank Tang Lei from Xi'an Microelectronics Technology Institute for his valuable comments to improve the quality of this paper.  ... 
doi:10.5281/zenodo.1125018 fatcat:tky2xdnbf5auzlcgjm3vfta7ue

Aerial Image Segmentation: A Survey

Gargi Bhattacharjee, Saswat K. Pujari
2017 International Journal of Applied Information Systems  
The main goal of image segmentation is to cluster the pixels of the regions corresponding to individual surfaces, objects, or natural parts of objects and to simplify and/or change the representation of  ...  In this paper, we have presented a study of various segmentation techniques applied on aerial images. The processes have been explained in detail followed by a comparative table.  ...  Mukhop adhyay Multi objective Genetic Clustering for Pixel Classification in Remote Sensing Imagery Pixel Classification of aerial images Fuzzy Clustering, Genetic Algorithm, Multi-Objective  ... 
doi:10.5120/ijais2017451702 fatcat:bp3e4et2sng5bcjrvzqk7qbgfm

Feature Selection Method Based on High-Resolution Remote Sensing Images and the Effect of Sensitive Features on Classification Accuracy

Yi Zhou, Rui Zhang, Shixin Wang, Futao Wang
2018 Sensors  
This paper proposes a novel feature selection approach, in which ReliefF, genetic algorithm, and support vector machine (RFGASVM) are integrated to extract buildings.  ...  After eliminating the sorted features, the feature subset and the C and γ parameters of support vector machine (SVM) are encoded into the chromosome of the genetic algorithm.  ...  Figure 8 . 8 Probability distribution density of different object features based on extraction from high-resolution images ((a) BJ-2 imagery, (b) UAV imagery, and (c) GF-2 imagery).  ... 
doi:10.3390/s18072013 pmid:29932436 pmcid:PMC6068868 fatcat:kjy5a6cnbvggjpmlzntkva5mxy

Page 2896 of Mathematical Reviews Vol. , Issue 2003d [page]

2003 Mathematical Reviews  
As ex- amples, we used binary vectors that represent text documents from different categories from the TIPSTER collection.  ...  Pal, Genetic algorithms, pattern classification and neural networks de- sign (347-384); A. Skowron and R. Swiniarski, Rough sets in pattern recognition (385-425); L. I.  ... 

Front Matter: Volume 10033

2016 Eighth International Conference on Digital Image Processing (ICDIP 2016)  
using a Base 36 numbering system employing both numerals and letters.  ...  SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model. A unique citation identifier (CID) number is assigned to each article at the time of publication.  ...  variance minimum algorithm SESSION 3 PATTERN RECOGNITION 0S Towards 3D object recognition with contractive autoencoders 10033 0U A new pixel-based granular fusion method for finger recognition  ... 
doi:10.1117/12.2257252 fatcat:v2ipfp2mp5gedjypzpecahpo7e

Multiclass Motor Imagery Recognition of Single Joint in Upper Limb Based on NSGA- II OVO TWSVM

Shan Guan, Kai Zhao, Fuwang Wang
2018 Computational Intelligence and Neuroscience  
This paper proposes a novel scheme that combined amplitude-frequency (AF) information of intrinsic mode function (IMF) with common spatial pattern (CSP), namely, AF-CSP to extract motor imagery (MI) features  ...  , and to improve classification performance, the second generation nondominated sorting evolutionary algorithm (NSGA-II) is used to tune hyperparameters for linear and nonlinear kernel one versus one twin  ...  The most widely used is the SMR BCI system based on motor imagery.  ... 
doi:10.1155/2018/6265108 pmid:30050566 pmcid:PMC6046167 fatcat:hdtbezrbdrbrvdnd7ydlcjaqim

Generative 3D images in a visual evolutionary computing system

Hong Liu
2010 Computer Science and Information Systems  
Then a binary tree based genetic algorithm is presented.  ...  This approach is illustrated by a 3D image generative example, which uses complex function expressions as chromosomes to form a binary tree, and all genetic operations are performed on the binary tree.  ...  Section 3 introduces genetic algorithms and genetic programming. In section 4, a binary tree based genetic algorithm is presented.  ... 
doi:10.2298/csis1001111l fatcat:cnmhvtwpjvdc5is3qa4zdujezm

Hybrid genetic optimization and statistical model based approach for the classification of shadow shapes in sonar imagery

M. Mignotte, C. Collet, P. Perez, P. Bouthemy
2000 IEEE Transactions on Pattern Analysis and Machine Intelligence  
AbstractÐWe present an original statistical classification method using a deformable template model to separate natural objects from man-made objects in an image provided by a high resolution sonar.  ...  In this context, we compare the results obtained with a deterministic relaxation technique (a gradient-based algorithm) and two stochastic relaxation methods: Simulated Annealing (SA) and a hybrid Genetic  ...  The main contribution of this paper lies in the use of deformable model to classify objects in sonar imagery.  ... 
doi:10.1109/34.825752 fatcat:irttqoqipnbvridkcbo55mxmdu

AN ENHANCEMENT REVIEW ON IMAGE SEGMENTATION METHODS

RV Santhi, E Ramaraj
2018 International Journal of Advanced Research  
Expectation-Maximization (EM) algorithm, OSTU and Genetic algorithms are used to demonstrate the synergy between the segmented images and object recognition.  ...  Central to this method is the combined use of image features from segmented objects and prior knowledge from historical thematic maps in a top-down segmentation procedure.  ... 
doi:10.21474/ijar01/6521 fatcat:5zsmpotkdzgbxbhidnqz56j5xe

Table of contents

2014 2014 International Conference on Informatics, Electronics & Vision (ICIEV)  
131 Analysis on Handwritten Bangla Character Recognition Using ANN 133 Developing a Cryptographic Algorithm Based on ASCII Conversions and a Cyclic Mathematical Function 134 Indexed Binary  ...  Direction of Migrating Procedural Paradigm to Object Based Architecture by forming Cluster of Functions using Local Search Heuristics 309 An Optimized Design of Binary Comparator Circuit in Quantum  ...  Implementation of vision based intelligent home automation and security system. 436 Analysis of the local frequency spectrum for the chirp signal 439 An Review of the e-JIKEI Network: Security camera system  ... 
doi:10.1109/iciev.2014.6850868 fatcat:y4gdctlg3zgajc3ge3drl6itcy

Subpixel Mapping Method of Hyperspectral Images Based on Modified Binary Quantum Particle Swarm Optimization

Shuhan Chen, Xiaorun Li, Liaoying Zhao
2017 Journal of Electrical and Computer Engineering  
This paper proposes a subpixel mapping method based on modified binary quantum particle swarm optimization (MBQPSO) to solve the above issues.  ...  To reduce time complexity, a target optimization strategy of global iteration combined with local iteration is performed.  ...  Immune clonal selection algorithms and differential evolution algorithms were used to solve the mathematical model using Verhoeye's data [22, 23] .  ... 
doi:10.1155/2017/2683248 fatcat:tesjvi5j7faepmor23g6onb7g4

Applied Imagery Pattern Recognition 2011

2011 2011 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)  
Abstract: Remote sensing imagery has been used in disaster response since Hurricane Camille in 1969; however limitations on the technology or our effective use of the information have prevented us from  ...  The Applied Imagery Pattern Recognition Workshop promotes and encourages the interdisciplinary interchange of ideas.  ...  Could these algorithms be used to classify and identify other objects, such as ships seen from electro-optical satellite imagery?  ... 
doi:10.1109/aipr.2011.6176381 fatcat:7bbefbxrnnfjvdtun4zixrckjy

Guest Editorial Introduction To The Special Issue On Automatic Target Detection And Recognition

B. Bhanu, D.E. Dudgeon, E.G. Zelnio, A. Rosenfeld, D. Casasent, I.S. Reed
1997 IEEE Transactions on Image Processing  
Munson and A. Bovik, for providing useful suggestions in the development of this special issue. We also extend our thanks to P. Wheeler and J. Handler for their support.  ...  We are grateful to the referees who spent their valuable time in reviewing the manuscripts and worked under a tight schedule.  ...  nets, and genetic algorithms.  ... 
doi:10.1109/tip.1997.552076 fatcat:hguhbyq5nffdxphleyqti5npyu

Introduction to the Special Issue on Learning in Computer Vision and Pattern Recognition

B. Bhanu, J. Peng, T. Huang, B. Draper
2005 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
Peng has served as the Program Co-Chair for the IEEE Workshop in Computer Vision and Pattern Recognition.  ...  ACKNOWLEDGMENT We thank the authors who submitted and contributed their work to this special issue and worked under a tight schedule.  ...  Synthetic aperture radar (SAR) imagery is used to demonstrate the results. The third paper, by Schneider et al., presents a biologically inspired hierarchical vision model for 3-D object recognition.  ... 
doi:10.1109/tsmcb.2005.847940 fatcat:avm2mj3cozaxxmqavlpseca5lm
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